[R] error in r

[Duncan Murdoch]

On 03/05/2014, 11:49 AM, thanoon younis wrote:
> dear all members
> i have error in the code below "Error in Y[i, 9] = 0.9 * XI[i, 2] + eps[9]
> : subscript out of bounds" is there anyone helps me please.

You created Y with 8 columns, then you refer to column 9.

Duncan Murdoch

>
> many thanks in advance
> thanoon
>
>
> llibrary(mvtnorm)   #Load mvtnorm package
> library(R2WinBUGS) #Load R2WinBUGS package
>
> N=500                         #Sample size
> BZ=numeric(N)                 #Fixed covariate in structural equation
> XI=matrix(NA, nrow=N, ncol=2) #Explanatory latent variables
> Eta=numeric(N)                #Outcome latent variables
> Y=matrix(NA, nrow=N, ncol=8)  #Observed variables
>
> #The covariance matrix of xi
> phi=matrix(c(1, 0.3, 0.3, 1), nrow=2)
>
> #Estimates and standard error estimates
> Eu=matrix(NA, nrow=100, ncol=10);    SEu=matrix(NA, nrow=100, ncol=10)
> Elam=matrix(NA, nrow=100, ncol=7);   SElam=matrix(NA, nrow=100, ncol=7)
> Eb=numeric(100);                     SEb=numeric(100)
> Egam=matrix(NA, nrow=100, ncol=5);   SEgam=matrix(NA, nrow=100, ncol=5)
> Esgm=matrix(NA, nrow=100, ncol=10);  SEsgm=matrix(NA, nrow=100, ncol=10)
> Esgd=numeric(100);                   SEsgd=numeric(100)
> Ephx=matrix(NA, nrow=100, ncol=3);   SEphx=matrix(NA, nrow=100, ncol=3)
>
> R=matrix(c(1.0, 0.3, 0.3, 1.0), nrow=2)
>
> parameters=c("u", "lam", "b", "gam", "sgm", "sgd", "phx")
>
> init1=list(u=rep(0,10), lam=rep(0,7), b=0, gam=rep(0,5), psi=rep(1,10),
>             psd=1, phi=matrix(c(1, 0, 0, 1), nrow=2))
>
> init2=list(u=rep(1,10), lam=rep(1,7), b=1, gam=rep(1,5), psi=rep(2,10),
>             psd=2, phi=matrix(c(2, 0, 0, 2), nrow=2))
>
> inits=list(init1, init2)
>
> eps=numeric(10)
>
> for (t in 1:100) {
>      #Generate Data
>      for (i in 1:N) {
>          BZ[i]=rt(1, 5)
>
>          XI[i,]=rmvnorm(1, c(0,0), phi)
>
>          delta=rnorm(1, 0, sqrt(0.36))
>          Eta[i]=0.5*BZ[i]+0.4*XI[i,1]+0.4*XI[i,2]+0.3*XI[i,1]*XI[i,2]
>                 +0.2*XI[i,1]*XI[i,1]+0.5*XI[i,2]*XI[i,2]+delta
>
>          eps[1:3]=rnorm(3, 0, sqrt(0.3))
>          eps[4:7]=rnorm(4, 0, sqrt(0.5))
>          eps[8:10]=rnorm(3, 0, sqrt(0.4))
>          Y[i,1]=Eta[i]+eps[1]
>          Y[i,2]=0.9*Eta[i]+eps[2]
>          Y[i,3]=0.7*Eta[i]+eps[3]
>          Y[i,4]=XI[i,1]+eps[4]
>          Y[i,5]=0.9*XI[i,1]+eps[5]
>          Y[i,6]=0.7*XI[i,1]+eps[6]
>          Y[i,7]=0.5*XI[i,1]+eps[7]
>          Y[i,8]=XI[i,2]+eps[8]
>          Y[i,9]=0.9*XI[i,2]+eps[9]
>          Y[i,10]=0.7*XI[i,2]+eps[10]
>      }
>
>      #Run WinBUGS
>      data=list(N=500, zero=c(0,0), z=BZ, R=R, y=Y)
>
>      model<-bugs(data,inits,parameters,
>                  model.file="C:/Simulation/model.txt",
>                  n.chains=2,n.iter=10000,n.burnin=4000,n.thin=1,
>                  bugs.directory="c:/Program Files/WinBUGS14/",
>                  working.directory="C:/Simulation/")
>
>      #Save Estimates
>      Eu[t,]=model$mean$u;               SEu[t,]=model$sd$u
>      Elam[t,]=model$mean$lam;           SElam[t,]=model$sd$lam
>      Eb[t]=model$mean$b;                SEb[t]=model$sd$b
>      Egam[t,]=model$mean$gam;           SEgam[t,]=model$sd$gam
>      Esgm[t,]=model$mean$sgm;           SEsgm[t,]=model$sd$sgm
>      Esgd[t]=model$mean$sgd;            SEsgd[t]=model$sd$sgd
>      Ephx[t,1]=model$mean$phx[1,1];     SEphx[t,1]=model$sd$phx[1,1]
>      Ephx[t,2]=model$mean$phx[1,2];     SEphx[t,2]=model$sd$phx[1,2]
>      Ephx[t,3]=model$mean$phx[2,2];     SEphx[t,3]=model$sd$phx[2,2]
> }
>
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