Chirs, this is brilliant! Thank you. It works as advertised.
I will have a look at the development version for running more than one MCMC chain. That could be quite useful to speed up things.
Cheers
Adel
Search found 63 matches
- Mon Oct 12, 2015 3:12 am
- Forum: R2MLwiN user forum
- Topic: Combining DoParrallel and R2mlwin
- Replies: 2
- Views: 4328
- Sat Oct 10, 2015 3:38 am
- Forum: R2MLwiN user forum
- Topic: Combining DoParrallel and R2mlwin
- Replies: 2
- Views: 4328
Combining DoParrallel and R2mlwin
Hi I am trying to work with the doParallel package (for multicore use) and R2mlwin. However, I am not able to pass the model specification as a list object via doParallel to the runmlwin function. I believe that the problems lay in how the list is defined: # (1) settings library(doParallel) library(...
- Wed Oct 07, 2015 1:50 am
- Forum: R2MLwiN user forum
- Topic: Specifying starting values behaves strangely
- Replies: 3
- Views: 8291
Re: Specifying starting values behaves strangely
Thanks Chris. Your suggestion works.
- Sat Oct 03, 2015 2:36 am
- Forum: R2MLwiN user forum
- Topic: Is there a “More” or Update option in R2mlwin?
- Replies: 1
- Views: 3363
Is there a “More” or Update option in R2mlwin?
What I would like to do is take an existing MCMC model and add more iterations to it. If I have (mymodel7 <- runMLwiN(normexam ~ 1 + standlrt + (1 | school) + (1 | student), estoptions = list(EstM = 1, mcmcMeth = list(burnin = 0, iterations = 500), startval = startval), data = tutorial)) Can I updat...
- Sat Oct 03, 2015 2:28 am
- Forum: R2MLwiN user forum
- Topic: Specifying starting values behaves strangely
- Replies: 3
- Views: 8291
Specifying starting values behaves strangely
Hi I am trying to specify starting values as this: a) test.mcmc2 <- runMLwiN(logit(AbsolutDep, cons) ~ 1 + DisVic + (1 | country) + (1 |CountryClusterHouse), D = "Binomial", estoptions = list(EstM = 0, debugmode=T, startval=list(FP.b = FP.b.my)), data = dfrm) b) This generates the followin...
- Wed Sep 30, 2015 6:44 pm
- Forum: R2MLwiN user forum
- Topic: r2mlwin output shows wrong number of higher levels, when subseiting the dataframe
- Replies: 1
- Views: 3408
r2mlwin output shows wrong number of higher levels, when subseiting the dataframe
Hi This is not a serious issue but can be confusing. R2mlwin output shows the wrong number of higher level units, when subsetting the dataframe and the higher level identifier is a factor. This is due to the fact that R keeps factor names even if they are unused. This means that one should use the d...
- Wed Sep 30, 2015 6:38 pm
- Forum: R2MLwiN user forum
- Topic: Specifying interaction terms for ordered response model
- Replies: 6
- Views: 7224
Re: Specifying interaction terms for ordered response model
Thanks Chris! I will have a look at it asap.
- Wed Sep 23, 2015 7:27 am
- Forum: R2MLwiN user forum
- Topic: Specifying interaction terms for ordered response model
- Replies: 6
- Views: 7224
Re: Specifying interaction terms for ordered response model
In your example with the * operator you have left in the main effects which shouldn't be necessary, I tried without the main effect but the function does not automatically insert them. Thanks for checking it with your own data as well. Please, let me know when you have an updated R2mlwin. cheers Adel
- Fri Sep 18, 2015 10:12 pm
- Forum: R2MLwiN user forum
- Topic: Specifying interaction terms for ordered response model
- Replies: 6
- Views: 7224
Re: Specifying interaction terms for ordered response model
Thanks for the reply. The suggestion did not work: > (runMLwiN(logit(AFgpWHO, cons, 3) ~ 1 + Price[1:2] + Mother_educ[1:2] + Price[1:2]*Mother_educ[1:2] + (1[1:2] | Region) , + D='Ordered Multinomial', estoptions=list(mcmcMeth = list(iterations = 100000, burnin=5000), resi.store =T, EstM=0),data = d...
- Fri Sep 18, 2015 5:11 am
- Forum: R2MLwiN user forum
- Topic: Specifying interaction terms for ordered response model
- Replies: 6
- Views: 7224
Specifying interaction terms for ordered response model
Hi I am trying to specify an interaction term for a logistic ordered response model in R2mlwin. My response has three categories. I am trying to interact one continues variable and one factor level variable. However, there is a strange behaviour when and where I add the extra term [1:2] to specify a...