R2MLwiN: Error while obeying batch file: Wrong number of output columns
Posted: Thu Oct 01, 2015 9:49 am
I'm trying to recreate MCMC Guide 06 with my data by setting up a random slopes model and then storing the residuals for prediction. I keep receiving the following error :
Error while obeying batch file... wrong number of output columns (full screen shot of error message attached).
Here's my code which sets up the data, specifies a variety of models (1-4), before focusing on how it's done in MCMC Guide 06. It's a three level model, with annual repeated broadband speed measurements (yrid), nested within local authorities (laid), nested within regions (rnid).
Data is attached = total.xlsx (sorry, it wouldn't let me upload the .csv!)
Any help would be much appreciated.
Error while obeying batch file... wrong number of output columns (full screen shot of error message attached).
Here's my code which sets up the data, specifies a variety of models (1-4), before focusing on how it's done in MCMC Guide 06. It's a three level model, with annual repeated broadband speed measurements (yrid), nested within local authorities (laid), nested within regions (rnid).
Data is attached = total.xlsx (sorry, it wouldn't let me upload the .csv!)
Any help would be much appreciated.
Code: Select all
mlwin = c("C:/Program Files (x86)/MLwiN v2.35/i386")
options(MLwiN_path = mlwin)
total<-read.csv("total.csv")
is.num <- sapply(total, is.numeric)
total[is.num] <- lapply(total[is.num], round, 2)
total$year <- total$year.num
## IGLS
(mymodel1 <- runMLwiN(speed ~ 1 + sfbb + (1| rnid) + (1 | laid) + (1 | yrid), data = total))
## Gibbs (with diffuse priors/gamma priors, as standard) (MCMC)
(mymodel2 <- runMLwiN(speed ~ 1 + sfbb + (1| rnid) + (1 | laid) + (1 | yrid), estoptions = list(EstM = 1), data = total))
## Diffuse priors (Uniform priors) (MCMC)
(mymodel3 <- runMLwiN(speed ~ 1 + sfbb + (1| rnid) + (1 | laid) + (1 | yrid), estoptions = list(EstM = 1, mcmcMeth = list(priorcode = 0)), data = total))
## slope at level 1 using sfbb (MCMC)
(mymodel4 <- runMLwiN(speed ~ 1 + sfbb + (1| rnid) +(1 | laid) + (1 + sfbb| yrid), estoptions = list(EstM = 1), data = total))
-------------------
#Follow guide 06
## Choose MCMC algoritm for estimation (IGLS will be used to obtain starting values for MCMC)
(mymodel6 <- runMLwiN(speed ~ 1 + sfbb + rnid + laid + rnid:sfbb + (1 | yrid), estoptions = list(EstM = 1), data = total))
## Define the model Choose IGLS algoritm for estimation Fit the model
(mymodel6.1 <- runMLwiN(speed ~ 1 + sfbb + (1 | rnid) + (1 | laid) + (1 + sfbb| yrid), data = total))
## Choose MCMC algoritm for estimation (IGLS will be used to obtain starting values for MCMC)
(mymodel6.20 <- runMLwiN(speed ~ 1 + sfbb + (1 | rnid) + (1 | laid) + (1 + sfbb| yrid), estoptions = list(EstM = 1, mcmcMeth = list(iterations = 5001), resi.store.levs= 2),data = total))