Hi. Mick,

 

Thanks much for your reply. Then, are the hidden parameters started with a random value and adjusted continuously as each iteration goes up? If so, due to the difference of the hidden parameters, each iteration is updated differently? Please correct me if I misunderstood.

 

Also, if you don’t mind, would it be fine to ask more questions? Related to my question, I’m still wondering if there is any way to restart the iteration once it is finished? Or if there is any way to speed up updates such as using multi-core (cpu)? I’m using only a single chain, not multi chains, so I doubt if multi-core would be applicable.

 

Thanks again and have a great weekend,

Ashley

 

 

 

 

On Sat, Feb 4, 2017 at 5:29 PM, Michael Mccarthy <[log in to unmask]> wrote:

Most MCMC sampling methods have additional parameters in them, other than the ones being estimated. These are hidden from user of OpenBUGS, and are used to tune the particular sampler being used to make it more efficient. So I don’t think what you are proposing will work, because those hidden parameters will need to re-tuned.

 

Regards,

 

Mick

-----------------

Michael McCarthy

School of BioSciences

The University of Melbourne

Parkville VIC 3010 Australia

 

+61 3 8344 6856

mickresearch.wordpress.com

qaeco.com

@mickresearch

 

 

 

From: (The BUGS software mailing list) [mailto:[log in to unmask]] On Behalf Of Ashley
Sent: Saturday, 4 February 2017 9:42 PM
To: [log in to unmask]
Subject: [BUGS] Setting up initial values with the last value in coda file

 

Hello. All in List,

 

My Openbugs code ran successfully with 20,000 updates, but results of convergence test showed that more updates are required. I’m thinking to extend the updates up to 50,000 (i.e., additional 30,000 updates). At this moment, because I already did 20,000 updates and don’t want to waste  time, I wondered what if I use the last values in coda files (which are saved in ‘State’ file) as initial values. If do so, can the first update from the second run be treated as 20,001th update? Thinking of how MCMC works, because the current estimates are obtained from the previous estimates and the first estimates are obtained from the initial values, I thought it might be ok. But, because I haven’t seen anything like that, I’d like to listen to your thoughts. Please let me know what I am missed.

 

Take care,

Ashley

------------------------------------------------------------------- This list is for discussion of modelling issues and the BUGS software. For help with crashes and error messages, first mail [log in to unmask] To mail the BUGS list, mail to [log in to unmask] Before mailing, please check the archive at www.jiscmail.ac.uk/lists/bugs.html Please do not mail attachments to the list. To leave the BUGS list, send LEAVE BUGS to [log in to unmask] If this fails, mail [log in to unmask], NOT the whole list

 

------------------------------------------------------------------- This list is for discussion of modelling issues and the BUGS software. For help with crashes and error messages, first mail [log in to unmask] To mail the BUGS list, mail to [log in to unmask] Before mailing, please check the archive at www.jiscmail.ac.uk/lists/bugs.html Please do not mail attachments to the list. To leave the BUGS list, send LEAVE BUGS to [log in to unmask] If this fails, mail [log in to unmask], NOT the whole list ------=_NextPart_000_006F_01D27F49.F7376AB0-- ========================================================================Date: Sat, 4 Feb 2017 17:01:37 +0000 Reply-To: "MILLARD, ANDREW R." <[log in to unmask]> Sender: "(The BUGS software mailing list)" <[log in to unmask]> From: "MILLARD, ANDREW R." <[log in to unmask]> Subject: Re: Setting up initial values with the last value in coda file Comments: To: Ashley <[log in to unmask]> In-Reply-To: <[log in to unmask]> Content-Type: text/plain; charset="us-ascii" Content-Transfer-Encoding: quoted-printable MIME-Version: 1.0 Message-ID: <[log in to unmask]> Yes this is a perfectly sensible way to extend an MCMC run. Best wishes Andrew -- Dr. Andrew Millard e: [log in to unmask] | t: +44 191 334 1147 w: https://www.dur.ac.uk/archaeology/staff/?id=160 https://www.dur.ac.uk/imems/ Director of the Institute of Medieval & Early Modern Studies, and Senior Lecturer in Archaeology, Durham University, UK > -----Original Message----- > From: (The BUGS software mailing list) [mailto:[log in to unmask]] On > Behalf Of Ashley > Sent: 04 February 2017 10:42 > To: [log in to unmask] > Subject: [BUGS] Setting up initial values with the last value in coda > file > > Hello. All in List, > > > > My Openbugs code ran successfully with 20,000 updates, but results of > convergence test showed that more updates are required. I'm thinking to > extend the updates up to 50,000 (i.e., additional 30,000 updates). At > this moment, because I already did 20,000 updates and don't want to > waste time, I wondered what if I use the last values in coda files > (which are saved in 'State' file) as initial values. If do so, can the > first update from the second run be treated as 20,001th update? Thinking > of how MCMC works, because the current estimates are obtained from the > previous estimates and the first estimates are obtained from the initial > values, I thought it might be ok. But, because I haven't seen anything > like that, I'd like to listen to your thoughts. Please let me know what > I am missed. > > > > Take care, > > Ashley > > ------------------------------------------------------------------- This > list is for discussion of modelling issues and the BUGS software. For > help with crashes and error messages, first mail [log in to unmask] > To mail the BUGS list, mail to [log in to unmask] Before mailing, > please check the archive at www.jiscmail.ac.uk/lists/bugs.html Please do > not mail attachments to the list. To leave the BUGS list, send LEAVE > BUGS to [log in to unmask] If this fails, mail bugs- > [log in to unmask], NOT the whole list ------------------------------------------------------------------- This list is for discussion of modelling issues and the BUGS software. For help with crashes and error messages, first mail [log in to unmask] To mail the BUGS list, mail to [log in to unmask] Before mailing, please check the archive at www.jiscmail.ac.uk/lists/bugs.html Please do not mail attachments to the list. To leave the BUGS list, send LEAVE BUGS to [log in to unmask] If this fails, mail [log in to unmask], NOT the whole list ========================================================================Date: Sun, 5 Feb 2017 17:36:02 -0500 Reply-To: [log in to unmask] Sender: "(The BUGS software mailing list)" <[log in to unmask]> From: Cory Atwood <[log in to unmask]> Subject: Re: Setting up initial values with the last value in coda file Comments: To: Ashley Lee <[log in to unmask]> In-Reply-To: <[log in to unmask]> MIME-Version: 1.0 Content-Type: multipart/alternative; boundary="------------B7CFD498DB7F942319788919" Message-ID: <[log in to unmask]> This is a multi-part message in MIME format. --------------B7CFD498DB7F942319788919 Content-Type: text/plain; charset=utf-8; format=flowed Content-Transfer-Encoding: quoted-printable I've never used the coda file for this, but I continue with more iterations all the time when the convergence isn't satisfactory. If I've used Update to create 20,000 iterations and the convergence doesn't look good enough, I go back into the Update window and tell it to do some more. Of course I don't exit from the BUGS program between the two updates. It never occurred to me that there was something wrong with this. Am I missing something? Cory On 2/5/2017 1:51 AM, Ashley Lee wrote: > > Hi. Mick, > > Thanks much for your reply. Then, are the hidden parameters started > with a random value and adjusted continuously as each iteration goes > up? If so, due to the difference of the hidden parameters, each > iteration is updated differently? Please correct me if I misunderstood. > > Also, if you don’t mind, would it be fine to ask more questions? > Related to my question, I’m still wondering if there is any way to > restart the iteration once it is finished? Or if there is any way to > speed up updates such as using multi-core (cpu)? I’m using only a > single chain, not multi chains, so I doubt if multi-core would be > applicable. > > Thanks again and have a great weekend, > > Ashley > > On Sat, Feb 4, 2017 at 5:29 PM, Michael Mccarthy > <[log in to unmask] > wrote: > > Most MCMC sampling methods have additional parameters in them, > other than the ones being estimated. These are hidden from user of > OpenBUGS, and are used to tune the particular sampler being used > to make it more efficient. So I don’t think what you are proposing > will work, because those hidden parameters will need to re-tuned. > > Regards, > > Mick > > ----------------- > > Michael McCarthy > > School of BioSciences > > The University of Melbourne > > Parkville VIC 3010 Australia > > +61 3 8344 6856 > > mickresearch.wordpress.com > > qaeco.com > > @mickresearch > > *From:*(The BUGS software mailing list) > [mailto:[log in to unmask] ] *On > Behalf Of *Ashley > *Sent:* Saturday, 4 February 2017 9:42 PM > *To:* [log in to unmask] > *Subject:* [BUGS] Setting up initial values with the last value in > coda file > > Hello. All in List, > > My Openbugs code ran successfully with 20,000 updates, but results > of convergence test showed that more updates are required. I’m > thinking to extend the updates up to 50,000 (i.e., additional > 30,000 updates). At this moment, because I already did 20,000 > updates and don’t want to waste time, I wondered what if I use > the last values in coda files (which are saved in ‘State’ file) as > initial values. If do so, can the first update from the second run > be treated as 20,001th update? Thinking of how MCMC works, because > the current estimates are obtained from the previous estimates and > the first estimates are obtained from the initial values, I > thought it might be ok. But, because I haven’t seen anything like > that, I’d like to listen to your thoughts. Please let me know what > I am missed. > > Take care, > > Ashley > > ------------------------------------------------------------------- > This list is for discussion of modelling issues and the BUGS > software. For help with crashes and error messages, first mail > [log in to unmask] To mail the > BUGS list, mail to [log in to unmask] > Before mailing, please check the > archive at www.jiscmail.ac.uk/lists/bugs.html > Please do not mail > attachments to the list. To leave the BUGS list, send LEAVE BUGS > to [log in to unmask] If > this fails, mail [log in to unmask] > , NOT the whole list > > ------------------------------------------------------------------- > This list is for discussion of modelling issues and the BUGS software. > For help with crashes and error messages, first mail > [log in to unmask] To mail the > BUGS list, mail to [log in to unmask] > Before mailing, please check the archive at > www.jiscmail.ac.uk/lists/bugs.html > Please do not mail > attachments to the list. To leave the BUGS list, send LEAVE BUGS to > [log in to unmask] If this > fails, mail [log in to unmask] > , NOT the whole list -- Cory Atwood Statwood Consulting 2905 Covington Rd Silver Spring, MD 20910 301-589-7158 ------------------------------------------------------------------- This list is for discussion of modelling issues and the BUGS software. For help with crashes and error messages, first mail [log in to unmask] To mail the BUGS list, mail to [log in to unmask] Before mailing, please check the archive at www.jiscmail.ac.uk/lists/bugs.html Please do not mail attachments to the list. To leave the BUGS list, send LEAVE BUGS to [log in to unmask] If this fails, mail [log in to unmask], NOT the whole list --------------B7CFD498DB7F942319788919 Content-Type: text/html; charset=utf-8 Content-Transfer-Encoding: quoted-printable

I've never used the coda file for this, but I continue with more iterations all the time when the convergence isn't satisfactory.  If I've used Update to create 20,000 iterations and the convergence doesn't look good enough, I go back into the Update window and tell it to do some more.  Of course I don't exit from the BUGS program between the two updates.  It never occurred to me that there was something wrong with this.  Am I missing something?

Cory


On 2/5/2017 1:51 AM, Ashley Lee wrote:
[log in to unmask]" type="cite">

Hi. Mick,

 

Thanks much for your reply. Then, are the hidden parameters started with a random value and adjusted continuously as each iteration goes up? If so, due to the difference of the hidden parameters, each iteration is updated differently? Please correct me if I misunderstood.

 

Also, if you don’t mind, would it be fine to ask more questions? Related to my question, I’m still wondering if there is any way to restart the iteration once it is finished? Or if there is any way to speed up updates such as using multi-core (cpu)? I’m using only a single chain, not multi chains, so I doubt if multi-core would be applicable.

 

Thanks again and have a great weekend,

Ashley

 

 

 

 

On Sat, Feb 4, 2017 at 5:29 PM, Michael Mccarthy <[log in to unmask]> wrote:

Most MCMC sampling methods have additional parameters in them, other than the ones being estimated. These are hidden from user of OpenBUGS, and are used to tune the particular sampler being used to make it more efficient. So I don’t think what you are proposing will work, because those hidden parameters will need to re-tuned.

 

Regards,

 

Mick

-----------------

Michael McCarthy

School of BioSciences

The University of Melbourne

Parkville VIC 3010 Australia

 

+61 3 8344 6856

mickresearch.wordpress.com

qaeco.com

@mickresearch

 

 

 

From: (The BUGS software mailing list) [mailto:[log in to unmask]] On Behalf Of Ashley
Sent: Saturday, 4 February 2017 9:42 PM
To: [log in to unmask]
Subject: [BUGS] Setting up initial values with the last value in coda file

 

Hello. All in List,

 

My Openbugs code ran successfully with 20,000 updates, but results of convergence test showed that more updates are required. I’m thinking to extend the updates up to 50,000 (i.e., additional 30,000 updates). At this moment, because I already did 20,000 updates and don’t want to waste  time, I wondered what if I use the last values in coda files (which are saved in ‘State’ file) as initial values. If do so, can the first update from the second run be treated as 20,001th update? Thinking of how MCMC works, because the current estimates are obtained from the previous estimates and the first estimates are obtained from the initial values, I thought it might be ok. But, because I haven’t seen anything like that, I’d like to listen to your thoughts. Please let me know what I am missed.

 

Take care,

Ashley

------------------------------------------------------------------- This list is for discussion of modelling issues and the BUGS software. For help with crashes and error messages, first mail [log in to unmask] To mail the BUGS list, mail to [log in to unmask] Before mailing, please check the archive at www.jiscmail.ac.uk/lists/bugs.html Please do not mail attachments to the list. To leave the BUGS list, send LEAVE BUGS to [log in to unmask] If this fails, mail [log in to unmask], NOT the whole list

 

------------------------------------------------------------------- This list is for discussion of modelling issues and the BUGS software. For help with crashes and error messages, first mail [log in to unmask] To mail the BUGS list, mail to [log in to unmask] Before mailing, please check the archive at www.jiscmail.ac.uk/lists/bugs.html Please do not mail attachments to the list. To leave the BUGS list, send LEAVE BUGS to [log in to unmask] If this fails, mail [log in to unmask], NOT the whole list

-- 
Cory Atwood
Statwood Consulting
2905 Covington Rd
Silver Spring, MD 20910
301-589-7158
------------------------------------------------------------------- This list is for discussion of modelling issues and the BUGS software. For help with crashes and error messages, first mail [log in to unmask] To mail the BUGS list, mail to [log in to unmask] Before mailing, please check the archive at www.jiscmail.ac.uk/lists/bugs.html Please do not mail attachments to the list. To leave the BUGS list, send LEAVE BUGS to [log in to unmask] If this fails, mail [log in to unmask], NOT the whole list --------------B7CFD498DB7F942319788919-- ========================================================================Date: Mon, 6 Feb 2017 09:29:58 +0000 Reply-To: Michael Mccarthy <[log in to unmask]> Sender: "(The BUGS software mailing list)" <[log in to unmask]> From: Michael Mccarthy <[log in to unmask]> Subject: Re: Setting up initial values with the last value in coda file Comments: To: "[log in to unmask]" <[log in to unmask]> In-Reply-To: <[log in to unmask]> MIME-Version: 1.0 Content-Type: multipart/alternative; boundary="_000_SY3PR01MB1577C97A6CC05148D9F3D173EE400SY3PR01MB1577ausp_" Message-ID: <[log in to unmask]> --_000_SY3PR01MB1577C97A6CC05148D9F3D173EE400SY3PR01MB1577ausp_ Content-Transfer-Encoding: base64 Content-Type: text/plain; charset=UTF-8 TXkgaW1wcmVzc2lvbiBmcm9tIEFzaGxleSB3YXMgdGhhdCBoZSBoYXMgc2F2ZWQgdGhlIGNvZGEg 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========================================================================Date: Mon, 6 Feb 2017 09:42:20 +0000 Reply-To: James Gallagher <[log in to unmask]> Sender: "(The BUGS software mailing list)" <[log in to unmask]> From: James Gallagher <[log in to unmask]> Subject: Short Courses at the SSC, University of Reading, UK (April and July 2017) Content-Type: text/plain; charset="iso-8859-1" Content-Transfer-Encoding: quoted-printable MIME-Version: 1.0 Message-ID: <[log in to unmask]> Dear list members,   Apologies for cross-posting. We are re-announcing the following short courses, which are scheduled to take place at the Statistical Services Centre in April and July 2017. Summary information is given below. For more detailed information and registration forms please see http://www.reading.ac.uk/ssc/, or email [log in to unmask] Please note Reading University's website is undergoing maintenance until the end of the year.  If you experience a problem please try again later. ******All of these courses include hands-on computer practical work******   Practical Bayesian Data Analysis View: http://www.reading.ac.uk/ssc/training/CourseDetails.php?name=Practical_Bayesian_Data_Analysis Duration: 3 days Date: 25-27 April 2017 Price: 995 GBP (a 30% academic discount is available; terms and conditions apply) Bayesian Survival Analysis View: http://www.reading.ac.uk/ssc/training/CourseDetails.php?name=Bayesian_Survival_Analysis Duration: 1 days Date: 14 July 2017 Price: 370 GBP (a 30% academic discount is available; terms and conditions apply) ******Location****** The Statistical Services Centre at Whiteknights campus, University of Reading is in a prime location in the South-East of England and has excellent transport links. The University is close to the M4 motorway allowing easy access by car.  Reading's railway station has high speed links to and from London Paddington, as well as regular services to and from other cities around the UK. There are direct services to and from both London Heathrow and London Gatwick Airports.  For further details view: http://www.reading.ac.uk/ssc/contact.php.   Kind Regards   James Gallagher Director Statistical Services Centre | University of Reading | PO Box 240 | RG6 6FN | United Kingdom +44 (0)118 378 6730 | www.reading.ac.uk/ssc | [log in to unmask] ------------------------------------------------------------------- This list is for discussion of modelling issues and the BUGS software. For help with crashes and error messages, first mail [log in to unmask] To mail the BUGS list, mail to [log in to unmask] Before mailing, please check the archive at www.jiscmail.ac.uk/lists/bugs.html Please do not mail attachments to the list. To leave the BUGS list, send LEAVE BUGS to [log in to unmask] If this fails, mail [log in to unmask], NOT the whole list ========================================================================Date: Mon, 6 Feb 2017 08:43:36 -0500 Reply-To: Lalita Thakali <[log in to unmask]> Sender: "(The BUGS software mailing list)" <[log in to unmask]> From: Lalita Thakali <[log in to unmask]> Subject: Problem in Installing OPENBUGS MIME-Version: 1.0 Content-Type: multipart/alternative; boundaryMessage-ID: [log in to unmask]> --001a114eed00e6ea660547dcd39a Content-Type: text/plain; charset=UTF-8 Hello all, I have a problem using OPENBUGS in my computer that has Windows 10. It does not get installed. I would appreciate if anyone has any suggestion on this. Thanks. -- Lalita ------------------------------------------------------------------- This list is for discussion of modelling issues and the BUGS software. For help with crashes and error messages, first mail [log in to unmask] To mail the BUGS list, mail to [log in to unmask] Before mailing, please check the archive at www.jiscmail.ac.uk/lists/bugs.html Please do not mail attachments to the list. To leave the BUGS list, send LEAVE BUGS to [log in to unmask] If this fails, mail [log in to unmask], NOT the whole list --001a114eed00e6ea660547dcd39a Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable
Hello all, 

I have a problem using OPENBUGS in my computer that has Windows 10. It does not get installed. I would appreciate if anyone has any suggestion on this. 

Thanks.

--

Lalita

------------------------------------------------------------------- This list is for discussion of modelling issues and the BUGS software. For help with crashes and error messages, first mail [log in to unmask] To mail the BUGS list, mail to [log in to unmask] Before mailing, please check the archive at www.jiscmail.ac.uk/lists/bugs.html Please do not mail attachments to the list. To leave the BUGS list, send LEAVE BUGS to [log in to unmask] If this fails, mail [log in to unmask], NOT the whole list --001a114eed00e6ea660547dcd39a-- ========================================================================Date: Wed, 8 Feb 2017 11:50:31 +0200 Reply-To: =?UTF-8?Q?emel_çankaya?= <[log in to unmask]> Sender: "(The BUGS software mailing list)" <[log in to unmask]> From: =?UTF-8?Q?emel_çankaya?= <[log in to unmask]> Subject: incomplete gamma function MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Message-ID: <[log in to unmask]> Dear all I deal with a distribution involving lower incomplete gamma function. For the likelihood definition in Bugs, is there a way of defining lower incomplete gamma function? Many thanks in advance Emel ------------------------------------------------------------------- This list is for discussion of modelling issues and the BUGS software. For help with crashes and error messages, first mail [log in to unmask] To mail the BUGS list, mail to [log in to unmask] Before mailing, please check the archive at www.jiscmail.ac.uk/lists/bugs.html Please do not mail attachments to the list. To leave the BUGS list, send LEAVE BUGS to [log in to unmask] If this fails, mail [log in to unmask], NOT the whole list ========================================================================Date: Thu, 9 Feb 2017 14:27:07 +0100 Reply-To: INGRID ROCHE <[log in to unmask]> Sender: "(The BUGS software mailing list)" <[log in to unmask]> From: INGRID ROCHE <[log in to unmask]> Subject: Ratio of empirical variances for the BYM model MIME-Version: 1.0 Content-Type: multipart/alternative; boundary="----=_Part_6139658_520803899.1486646827795" Message-ID: <[log in to unmask]> ------=_Part_6139658_520803899.1486646827795 Content-Type: text/plain; charset=utf-8 Content-Transfer-Encoding: quoted-printable Dear list-members, I’m working on the spatial repartition of cancer incident data. For this, I apply the BYM spatial model. I’d like to evaluate which of the unstructured or structured heterogeneity is better for describing the great part of the spatial variability of the incident rates. My aim is to compare the ratio of the empirical variance of this two components, directly with the WinBUGS software. Basically, I try to make this with the following code for the BYM model : model { for (i in 1 : I) { O[i] ~ dpois(mu[i]) log(mu[i]) <- log(E[i]) + alpha + H[i] + S[i] SMR[i] <- O[i]/E[i] RR[i] <- exp(alpha + H[i] + S[i]) PP[i] <- step(RR[i] - 1) PM[i] <- step(1 - RR[i]) H[i] ~ dnorm(0.0, prec) } S[1:I] ~ car.normal(adj[], weights[], num[], precstar) alpha ~ dflat() prec ~ dgamma(0.01, 0.001) precstar ~ dgamma(0.01, 0.001) vhet <- 1 / sqrt(prec) vgeo <- 1 / sqrt(precstar) mean <- exp(alpha) sd.emph <- sd(H[]) v.emph <- pow(sd.emph,2) sd.emps <- sd(S[]) v.emps <- pow(sd.emps,2) ratiov <- v.emps/ v.emph } My results are the following: Node statistics node mean sd MC error 2.5% median 97.5% start sample ratiov 0.398 1.791 0.06343 0.007514 0.09071 2.664 20000 40001 v.emph 0.03133 0.01752 5.882E-4 0.002075 0.03047 0.06823 20000 40001 v.emps 0.004231 0.005065 2.143E-4 2.905E-4 0.002544 0.01905 20000 40001 I don’t know exactly how this ratio is computed and if it is the exact way of calculating it with the credible intervals, using the WinBUGS software. Any advice will be welcome. Best regards, Ingrid ROCHE Ph.D Student -Grenoble-Alpes University Laboratoire TIMC - IMAG, Equipe BCM Registre des cancers de l'Isère CHU Grenoble - Pavillon E BP 217 38043 Grenoble cedex 9 ------------------------------------------------------------------- This list is for discussion of modelling issues and the BUGS software. For help with crashes and error messages, first mail [log in to unmask] To mail the BUGS list, mail to [log in to unmask] Before mailing, please check the archive at www.jiscmail.ac.uk/lists/bugs.html Please do not mail attachments to the list. To leave the BUGS list, send LEAVE BUGS to [log in to unmask] If this fails, mail [log in to unmask], NOT the whole list ------=_Part_6139658_520803899.1486646827795 Content-Type: text/html; charset=utf-8 Content-Transfer-Encoding: quoted-printable

Dear list-members,

 

 

I’m working on the spatial repartition of cancer incident data. For this, I apply the BYM spatial model. I’d like to evaluate which of the unstructured or structured heterogeneity is better for describing the great part of the spatial variability of the incident rates. My aim is to compare the ratio of the empirical variance of this two components, directly with the WinBUGS software.

 

 

 

Basically, I try to make this with the following code for the BYM model :

 

model {

  for (i in 1 : I) {

    O[i] ~   dpois(mu[i])

    log(mu[i]) <-  log(E[i])  + alpha  + H[i] + S[i]

    SMR[i] <-  O[i]/E[i]

    RR[i] <-  exp(alpha  + H[i] + S[i])

    PP[i] <-  step(RR[i] - 1)

    PM[i] <-  step(1 - RR[i])

    H[i] ~   dnorm(0.0, prec)

  }

 

  S[1:I] ~ car.normal(adj[], weights[], num[], precstar)

 

  alpha    ~  dflat()

  prec     ~  dgamma(0.01, 0.001)

  precstar ~  dgamma(0.01, 0.001)

 

  vhet  <-  1 / sqrt(prec)

  vgeo  <-  1 / sqrt(precstar)

  mean  <-  exp(alpha)

 

  sd.emph  <-  sd(H[])

  v.emph   <-  pow(sd.emph,2)

  sd.emps  <-  sd(S[])

  v.emps   <-  pow(sd.emps,2)

  ratiov   <-  v.emps/ v.emph 

}

 

 

 

 

My results are the following:


Node statistics

                node       mean     sd          MC error               2.5%       median   97.5%     start        sample

                ratiov      0.398     1.791       0.06343   0.007514 0.09071   2.664       20000      40001

                v.emph   0.03133   0.01752   5.882E-4 0.002075 0.03047   0.06823   20000      40001

                v.emps   0.004231 0.005065 2.143E-4 2.905E-4 0.002544 0.01905   20000      40001

 

 

 

 

I don’t know exactly how this ratio is computed and if it is the exact way of calculating it with the credible intervals, using the WinBUGS software.

 

Any advice will be welcome.

Best regards,



Ingrid ROCHE

Ph.D Student -Grenoble-Alpes University

 

Laboratoire TIMC - IMAG, Equipe BCM

Registre des cancers de l'Isère

 

CHU Grenoble - Pavillon E

BP 217

38043 Grenoble cedex 9



------------------------------------------------------------------- This list is for discussion of modelling issues and the BUGS software. For help with crashes and error messages, first mail [log in to unmask] To mail the BUGS list, mail to [log in to unmask] Before mailing, please check the archive at www.jiscmail.ac.uk/lists/bugs.html Please do not mail attachments to the list. To leave the BUGS list, send LEAVE BUGS to [log in to unmask] If this fails, mail [log in to unmask], NOT the whole list ------=_Part_6139658_520803899.1486646827795-- ========================================================================Date: Wed, 15 Feb 2017 09:53:35 +0200 Reply-To: Polychronis KOSTOULAS <[log in to unmask]> Sender: "(The BUGS software mailing list)" <[log in to unmask]> From: Polychronis KOSTOULAS <[log in to unmask]> Subject: LCMATE mailing list Content-Type: text/plain; charset=UTF-8; format=flowed; DelSp=Yes MIME-Version: 1.0 Content-Disposition: inline Content-Transfer-Encoding: quoted-printable Message-ID: <[log in to unmask]> Dear colleagues, We have created LCMATE (Latent Class Models for the Accuracy of TEsts), a mailing list for people that are interested in the development and application of latent class models for the evaluation of diagnostic tests, primarily within a Bayesian framework. The focus is on estimating the diagnostic accuracy of tests (either dichotomous, ordinal or continuous) in the absence of a gold standard. LCMs are used within this context because the true disease status of the individuals/samples is unknown (i.e. latent, or hidden). The scope of this list is to: 1. Assist researchers that are interested in the application of these methods to their own data 2. Promote the exchange of knowledge and ideas between researchers working in this area To subscribe please visit: http://lists.uth.gr/mailman/listinfo/lcmate or send an email to: [log in to unmask] Kind Regards, Polychronis Kostoulas LCMATE Administrator   ------------------------------------------------------------------- This list is for discussion of modelling issues and the BUGS software. For help with crashes and error messages, first mail [log in to unmask] To mail the BUGS list, mail to [log in to unmask] Before mailing, please check the archive at www.jiscmail.ac.uk/lists/bugs.html Please do not mail attachments to the list. To leave the BUGS list, send LEAVE BUGS to [log in to unmask] If this fails, mail [log in to unmask], NOT the whole list ========================================================================Date: Tue, 21 Feb 2017 10:16:12 +0000 Reply-To: Robert Goudie <[log in to unmask]> Sender: "(The BUGS software mailing list)" <[log in to unmask]> From: Robert Goudie <[log in to unmask]> Subject: COURSE: Bayesian analysis, MCMC and BUGS - MRC Biostatistics Unit, University of Cambridge Content-Type: text/plain; charset=us-ascii Content-Transfer-Encoding: quoted-printable Mime-Version: 1.0 (Mac OS X Mail 10.2 \(3259\)) Message-ID: <[log in to unmask]> SHORT COURSE: Introduction to Bayesian statistics using BUGS Thu 30th March 2017 - Fri 31st March 2017 (2 days) MRC Biostatistics Unit, University of Cambridge, UK Course instructors: Dr Robert Goudie, Dr Anne Presanis, and Dr Dan Jackson (MRC Biostatistics Unit) Target audience: * Statisticians working in any application area, with familiarity of classical methods such as generalised linear and random-effects modelling. * No experience of Bayesian methods or specialist software will be assumed. Course aims: * This course is intended to provide an introduction to Bayesian analysis and MCMC methods, and a fairly detailed tutorial on the use of OpenBUGS/JAGS/WinBUGS. * Day 1 - Introduction to the use of Monte Carlo methods, Bayesian methods, Markov chain Monte Carlo (MCMC), regression models, and implementation in OpenBUGS/WinBUGS or JAGS/OpenBUGS/WinBUGS via R. * Day 2 - Generalised linear models, predictions, missing data, model criticism, model comparison and assessing sensitivity to prior distributions, introduction to hierarchical models. * The emphasis throughout will be on practical examples: software and code to carry out all the analyses will be provided. Participants are encouraged to bring their own laptops for the practicals. Course fees include a copy of The BUGS Book (Lunn et al., 2013). For further information see http://www.mrc-bsu.cam.ac.uk/bayescourse Registration now open - for registration see http://onlinesales.admin.cam.ac.uk/browse/extra_info.asp?modid=2&prodid=1793 For further information about the BSU Short Courses please contact Sharon Dippenaar (BSU Course Administrator) Telephone: +44 (0) 1223 330366 E-mail: [log in to unmask] ------------------------------------------------------------------- This list is for discussion of modelling issues and the BUGS software. For help with crashes and error messages, first mail [log in to unmask] To mail the BUGS list, mail to [log in to unmask] Before mailing, please check the archive at www.jiscmail.ac.uk/lists/bugs.html Please do not mail attachments to the list. To leave the BUGS list, send LEAVE BUGS to [log in to unmask] If this fails, mail [log in to unmask], NOT the whole list ========================================================================Date: Thu, 23 Feb 2017 22:47:06 +0300 Reply-To: =?UTF-8?Q?Sedat_Şen?= <[log in to unmask]> Sender: "(The BUGS software mailing list)" <[log in to unmask]> From: =?UTF-8?Q?Sedat_Şen?= <[log in to unmask]> Subject: Easy way to generate data sets using WINBUGS MIME-Version: 1.0 Content-Type: multipart/alternative; boundaryMessage-ID: <[log in to unmask]> --001a114420e824a56c054937e38c Content-Type: text/plain; charset=UTF-8 Dear list members, I have a multilevel IRT model code and pre-defined values for item difficulty parameters. I want to generate 1200 data sets using this model and pre-defined values (number of schools, sample size and number of items). As far as I know this can be achieved in WinBUGS using save state option under model menu. What I did was just compiling the following code and pre-defined values and saving states (which inludes categorical data sets) after each update. This is very tedious and time-consuming for me given that I need to generate 1200 data sets. I was wondering if there is an easier and faster way to generate data sets within WinBUGS. I want to generate 1200 data sets at one time. Does any of you have a suggestion? *This is my code:* model { # G=2 for (j in 1:N) { for (i in 1:T) { logit(p2[j,i]) <- a2[gmem2[j], ggmem2[group[j]]] *u22[j] - b2[i,gmem2[j],ggmem2[group[j]]] r2[j,i]~dbern(p2[j,i]) }} # Ability for (j in 1:N) { u22[j]~dnorm(mu22[gmem2[j],ggmem2[group[j]]],1) } for (g in 1:G2) { for (k in 1:K2){ mu22[g,k] ~ dnorm(0,1) }} mu22[1,1] <- 0 #SD of Ability for (g in 1:G2) { for (k in 1:K2){ a2[g, k] ~ dnorm(0,1) I(0,) }} # Student Level for (j in 1:N) { gmem2[j] ~ dcat(pi2[ggmem2[group[j]],1:G2]) } for (s in 1:S){ pi2[s, 1:G2] ~ ddirch(alpha2[]) } # School Level for (s in 1:S){ ggmem2[s] ~ dcat(pi21[1:K2]) } pi21[1:K2] ~ ddirch(alpha21[]) b2[1,1,1] <- -1.654 b2[1,1,2] <- -1.72 b2[1,2,1] <- -1.8 b2[1,2,2] <- -0.7434 b2[2,1,1] <- -1.03 b2[2,1,2] <- 0.4278 b2[2,2,1] <- -0.1657 b2[2,2,2] <- -0.7066 b2[3,1,1] <- -2.0328 b2[3,1,2] <- -0.7481 b2[3,2,1] <- -1.288 b2[3,2,2] <- -0.9759 b2[4,1,1] <- -1.958 b2[4,1,2] <- -0.293 b2[4,2,1] <- 0.06021 b2[4,2,2] <- -0.3805 b2[5,1,1] <- -1.509 b2[5,1,2] <- 0.1729 b2[5,2,1] <- 0.1288 b2[5,2,2] <- 0.4044 b2[6,1,1] <- -1.845 b2[6,1,2] <- -0.2965 b2[6,2,1] <- -0.6138 b2[6,2,2] <- -0.2659 b2[7,1,1] <- -1.172 b2[7,1,2] <- 0.7925 b2[7,2,1] <- 0.4889 b2[7,2,2] <- 0.2158 b2[8,1,1] <- -2.511 b2[8,1,2] <- -0.7819 b2[8,2,1] <- 0.3679 b2[8,2,2] <- 1.047 b2[9,1,1] <- -1.502 b2[9,1,2] <- -1.535 b2[9,2,1] <- -0.7474 b2[9,2,2] <- 0.231 b2[10,1,1] <- -1.718 b2[10,1,2] <- -0.7058 b2[10,2,1] <- -0.5551 b2[10,2,2] <- 0.3631 b2[11,1,1] <- -0.4231 b2[11,1,2] <- 0.95 b2[11,2,1] <- 0.3513 b2[11,2,2] <- 0.166 b2[12,1,1] <- -0.6774 b2[12,1,2] <- 1.277 b2[12,2,1] <- 1.509 b2[12,2,2] <- 0.8955 b2[13,1,1] <- -1.757 b2[13,1,2] <- 0.8907 b2[13,2,1] <- 0.8363 b2[13,2,2] <- 0.2991 b2[14,1,1] <- -2.26 b2[14,1,2] <- -0.62 b2[14,2,1] <- -0.9972 b2[14,2,2] <- -0.3555 b2[15,1,1] <- -1.456 b2[15,1,2] <- 0.387 b2[15,2,1] <- 0.4786 b2[15,2,2] <- 0.4905 b2[16,1,1] <- -1.41 b2[16,1,2] <- -0.3934 b2[16,2,1] <- 0.2874 b2[16,2,2] <- 0.331 b2[17,1,1] <- -1.073 b2[17,1,2] <- 0.5976 b2[17,2,1] <- 0.7708 b2[17,2,2] <- 0.1031 b2[18,1,1] <- -1.85 b2[18,1,2] <- 0.5892 b2[18,2,1] <- 0.6991 b2[18,2,2] <- 0.1877 b2[19,1,1] <- -1.365 b2[19,1,2] <- -1.245 b2[19,2,1] <- -1.275 b2[19,2,2] <- -0.5721 b2[20,1,1] <- -1.138 b2[20,1,2] <- 0.9489 b2[20,2,1] <- 0.5573 b2[20,2,2] <- -0.2604 } #pre-defined values for sample size and number of schools list(N00, T , SP, G2=2, K2=2, alpha2=c(1,1), alpha21=c(1,1), group=c(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1, 2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2, 3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3, 4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4, 5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5, 6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6, 7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7, 8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8, 9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9, 10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10, 11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11, 12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12, 13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13, 14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14, 15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15, 16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16, 17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17, 18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18, 19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19, 20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20, 21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21, 22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22, 23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23, 24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24, 25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25, 26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26, 27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27, 28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28, 29,29,29,29,29,29,29,29,29,29,29,29,29,29,29,29,29,29,29,29,29,29,29,29,29,29,29,29,29,29, 30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30, 31,31,31,31,31,31,31,31,31,31,31,31,31,31,31,31,31,31,31,31,31,31,31,31,31,31,31,31,31,31, 32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32, 33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33, 34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34, 35,35,35,35,35,35,35,35,35,35,35,35,35,35,35,35,35,35,35,35,35,35,35,35,35,35,35,35,35,35, 36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36, 37,37,37,37,37,37,37,37,37,37,37,37,37,37,37,37,37,37,37,37,37,37,37,37,37,37,37,37,37,37, 38,38,38,38,38,38,38,38,38,38,38,38,38,38,38,38,38,38,38,38,38,38,38,38,38,38,38,38,38,38, 39,39,39,39,39,39,39,39,39,39,39,39,39,39,39,39,39,39,39,39,39,39,39,39,39,39,39,39,39,39, 40,40,40,40,40,40,40,40,40,40,40,40,40,40,40,40,40,40,40,40,40,40,40,40,40,40,40,40,40,40, 41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41, 42,42,42,42,42,42,42,42,42,42,42,42,42,42,42,42,42,42,42,42,42,42,42,42,42,42,42,42,42,42, 43,43,43,43,43,43,43,43,43,43,43,43,43,43,43,43,43,43,43,43,43,43,43,43,43,43,43,43,43,43, 44,44,44,44,44,44,44,44,44,44,44,44,44,44,44,44,44,44,44,44,44,44,44,44,44,44,44,44,44,44, 45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45, 46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46, 47,47,47,47,47,47,47,47,47,47,47,47,47,47,47,47,47,47,47,47,47,47,47,47,47,47,47,47,47,47, 48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48, 49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49, 50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50)) ------------------------------------------------------------------- This list is for discussion of modelling issues and the BUGS software. For help with crashes and error messages, first mail [log in to unmask] To mail the BUGS list, mail to [log in to unmask] Before mailing, please check the archive at www.jiscmail.ac.uk/lists/bugs.html Please do not mail attachments to the list. To leave the BUGS list, send LEAVE BUGS to [log in to unmask] If this fails, mail [log in to unmask], NOT the whole list --001a114420e824a56c054937e38c Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable
Dear list members,

I have a multilevel IRT model code and pre-defined values for item difficulty parameters. I want to generate 1200 data sets using this model and pre-defined values (number of schools, sample size and number of items). As far as I know this can be achieved in WinBUGS using save state option under model menu. What I did was just compiling the following code and pre-defined values and saving states (which inludes categorical data sets) after each update. This is very tedious and time-consuming for me given that I need to generate 1200 data sets. I was wondering if there is an easier and faster way to generate data sets within WinBUGS. I want to generate 1200 data sets at one time. Does any of you have a suggestion?

This is my code:


model 
{


# G=2

for (j in 1:N) {
    for (i in 1:T) {     
     logit(p2[j,i]) <-  a2[gmem2[j], ggmem2[group[j]]] *u22[j]  - b2[i,gmem2[j],ggmem2[group[j]]] 
     r2[j,i]~dbern(p2[j,i])
}}



# Ability
for (j in 1:N) { 
        u22[j]~dnorm(mu22[gmem2[j],ggmem2[group[j]]],1)
}
 



for (g in 1:G2) {
    for (k in 1:K2){
    mu22[g,k] ~ dnorm(0,1)  
}}



mu22[1,1] <- 0

#SD of Ability
for (g in 1:G2) {
        for (k in 1:K2){
        a2[g, k] ~ dnorm(0,1) I(0,)
}}

# Student Level
for (j in 1:N) {
     gmem2[j] ~ dcat(pi2[ggmem2[group[j]],1:G2])
}

for (s in 1:S){
pi2[s, 1:G2] ~ ddirch(alpha2[])
} 



# School Level
for (s in 1:S){
    ggmem2[s] ~ dcat(pi21[1:K2])
}   

pi21[1:K2] ~ ddirch(alpha21[])

b2[1,1,1] <- -1.654
b2[1,1,2] <- -1.72
b2[1,2,1] <- -1.8
b2[1,2,2] <- -0.7434
b2[2,1,1] <- -1.03
b2[2,1,2] <- 0.4278
b2[2,2,1] <- -0.1657
b2[2,2,2] <- -0.7066
b2[3,1,1] <- -2.0328
b2[3,1,2] <- -0.7481
b2[3,2,1] <- -1.288
b2[3,2,2] <- -0.9759
b2[4,1,1] <- -1.958
b2[4,1,2] <- -0.293
b2[4,2,1] <- 0.06021
b2[4,2,2] <- -0.3805
b2[5,1,1] <- -1.509
b2[5,1,2] <- 0.1729
b2[5,2,1] <- 0.1288
b2[5,2,2] <- 0.4044
b2[6,1,1] <- -1.845
b2[6,1,2] <- -0.2965
b2[6,2,1] <- -0.6138
b2[6,2,2] <- -0.2659
b2[7,1,1] <- -1.172
b2[7,1,2] <- 0.7925
b2[7,2,1] <- 0.4889
b2[7,2,2] <- 0.2158
b2[8,1,1] <- -2.511
b2[8,1,2] <- -0.7819
b2[8,2,1] <- 0.3679
b2[8,2,2] <- 1.047
b2[9,1,1] <- -1.502
b2[9,1,2] <- -1.535
b2[9,2,1] <- -0.7474
b2[9,2,2] <- 0.231
b2[10,1,1] <- -1.718
b2[10,1,2] <- -0.7058
b2[10,2,1] <- -0.5551
b2[10,2,2] <- 0.3631
b2[11,1,1] <- -0.4231
b2[11,1,2] <- 0.95
b2[11,2,1] <- 0.3513
b2[11,2,2] <- 0.166
b2[12,1,1] <- -0.6774
b2[12,1,2] <- 1.277
b2[12,2,1] <- 1.509
b2[12,2,2] <- 0.8955
b2[13,1,1] <- -1.757
b2[13,1,2] <- 0.8907
b2[13,2,1] <- 0.8363
b2[13,2,2] <- 0.2991
b2[14,1,1] <- -2.26
b2[14,1,2] <- -0.62
b2[14,2,1] <- -0.9972
b2[14,2,2] <- -0.3555
b2[15,1,1] <- -1.456
b2[15,1,2] <- 0.387
b2[15,2,1] <- 0.4786
b2[15,2,2] <- 0.4905
b2[16,1,1] <- -1.41
b2[16,1,2] <- -0.3934
b2[16,2,1] <- 0.2874
b2[16,2,2] <- 0.331
b2[17,1,1] <- -1.073
b2[17,1,2] <- 0.5976
b2[17,2,1] <- 0.7708
b2[17,2,2] <- 0.1031
b2[18,1,1] <- -1.85
b2[18,1,2] <- 0.5892
b2[18,2,1] <- 0.6991
b2[18,2,2] <- 0.1877
b2[19,1,1] <- -1.365
b2[19,1,2] <- -1.245
b2[19,2,1] <- -1.275
b2[19,2,2] <- -0.5721
b2[20,1,1] <- -1.138
b2[20,1,2] <- 0.9489
b2[20,2,1] <- 0.5573
b2[20,2,2] <- -0.2604


}



#pre-defined values for sample size and number of schools

list(N=1500, T=20,  S=50, G2=2, K2=2,  
alpha2=c(1,1), alpha21=c(1,1),
group=c(1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,
2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,2,
3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,
4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,4,
5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,5,
6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,6,
7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,7,
8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,
9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,9,
10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,10,
11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,11,
12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,
13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,13,
14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,14,
15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,15,
16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,
17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,17,
18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,18,
19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,19,
20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,
21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,21,
22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,22,
23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,23,
24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,
25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,25,
26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,26,
27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,27,
28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,
29,29,29,29,29,29,29,29,29,29,29,29,29,29,29,29,29,29,29,29,29,29,29,29,29,29,29,29,29,29,
30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,30,
31,31,31,31,31,31,31,31,31,31,31,31,31,31,31,31,31,31,31,31,31,31,31,31,31,31,31,31,31,31,
32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,
33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,33,
34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,34,
35,35,35,35,35,35,35,35,35,35,35,35,35,35,35,35,35,35,35,35,35,35,35,35,35,35,35,35,35,35,
36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,
37,37,37,37,37,37,37,37,37,37,37,37,37,37,37,37,37,37,37,37,37,37,37,37,37,37,37,37,37,37,
38,38,38,38,38,38,38,38,38,38,38,38,38,38,38,38,38,38,38,38,38,38,38,38,38,38,38,38,38,38,
39,39,39,39,39,39,39,39,39,39,39,39,39,39,39,39,39,39,39,39,39,39,39,39,39,39,39,39,39,39,
40,40,40,40,40,40,40,40,40,40,40,40,40,40,40,40,40,40,40,40,40,40,40,40,40,40,40,40,40,40,
41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,41,
42,42,42,42,42,42,42,42,42,42,42,42,42,42,42,42,42,42,42,42,42,42,42,42,42,42,42,42,42,42,
43,43,43,43,43,43,43,43,43,43,43,43,43,43,43,43,43,43,43,43,43,43,43,43,43,43,43,43,43,43,
44,44,44,44,44,44,44,44,44,44,44,44,44,44,44,44,44,44,44,44,44,44,44,44,44,44,44,44,44,44,
45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,45,
46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,46,
47,47,47,47,47,47,47,47,47,47,47,47,47,47,47,47,47,47,47,47,47,47,47,47,47,47,47,47,47,47,
48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,48,
49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,49,
50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50,50))
------------------------------------------------------------------- This list is for discussion of modelling issues and the BUGS software. For help with crashes and error messages, first mail [log in to unmask] To mail the BUGS list, mail to [log in to unmask] Before mailing, please check the archive at www.jiscmail.ac.uk/lists/bugs.html Please do not mail attachments to the list. To leave the BUGS list, send LEAVE BUGS to [log in to unmask] If this fails, mail [log in to unmask], NOT the whole list --001a114420e824a56c054937e38c--