Firstly, you both need to subscribe to the mailing list.  Please go to
https://stat.ethz.ch/mailman/listinfo/r-help and subscribe.  In this way
you will also get emails from people asking questions and may benefit or
even contribute help to another.  There are several other specialty help
lists that may or may not benefit you.

As for your package installation problem it is difficult to say at this
point.  It installs perfectly fine for me.

1. Do any of the dependencies install or none at all?
2. How are you installing (install.packages or Rstudio interface)?
3. What is your R version?

Charles


On Sat, Jun 7, 2014 at 9:23 AM, Yijia Wang <yw1468@nyu.edu> wrote:

> Hi Charles,
>
> I sent my message to the mail you said, but was rejected and I can't
> figure out why, and here is my problem:
>
> when I install fGarch package, I got the following error message:
>
> Warning in install.packages :
>   unable to access index for repository
> http://cran.rstudio.com/bin/windows/contrib/3.0
> Warning in install.packages :
>   unable to access index for repository
> http://www.stats.ox.ac.uk/pub/RWin/bin/windows/contrib/3.0
> Error in install.packages : cannot open the connection
>
> Could you please give me some advice on how to fix it?
>
> Many thanks~
>
>
> On Sat, Jun 7, 2014 at 6:41 AM, Charles Determan Jr <deter088@umn.edu>
> wrote:
>
>> REPLY TO ALL FOR THE R-HELP LIST!!!
>>
>> I apologize for the bluntness but you must realize that it is critical if
>> you desire to get help on the mailing list beyond a single person your
>> question must actually get to the mailing list.  My expertise only goes so
>> far and there is an infinitely larger community that could likely help you
>> more quickly and often in a way that can increase performance.  I am
>> always
>> happy to help when time allows but please make sure the
>> r-help@r-project.org
>> is a recipient as well.
>>
>> Regarding your code, after glancing at it again it is clear that you
>> aren't
>> actually submitting a covariance matrix to mvrnorm.  The only place you
>> specify phi1 is initially with NA's and then within the list init1.  If
>> you
>> intend to use the list init1 you specify it within the function call:
>>
>> xi1<-mvrnorm(1,c(0,0,0,0),init1$phi1, tol = 1e-6, empirical = FALSE,
>> EISPACK = FALSE)
>>
>> Once again, please make sure you are not just sending these messages
>> solely
>> to me.
>>
>> Regards,
>> Charles
>>
>>
>> On Thu, Jun 5, 2014 at 9:04 AM, thanoon younis <
>> thanoon.younis80@gmail.com>
>> wrote:
>>
>> > many thanks to you Dr. Charles
>> >
>> > Really i have a problem with simulation data in xi  and now i have this
>> > erro r   "Error in mvrnorm(1, c(0, 0, 0), phi1, tol = 1e-06, empirical =
>> > FALSE,  :   incompatible arguments"
>> >
>> > Regards
>> >
>> >
>> >
>> >
>> > On 5 June 2014 16:45, Charles Determan Jr <deter088@umn.edu> wrote:
>> >
>> >> Hello again Thanoon,
>> >>
>> >> Once again, you should send these request not to me but to the r-help
>> >> list.  You are far more likely to get help from the greater R community
>> >> than just me.  Furthermore, it is not entirely clear where your error
>> is.
>> >> It is courteous to provide only the code that is run up to the error
>> and
>> >> commenting the location.  I see you have a loop and all the more
>> important
>> >> to isolate where the error is taking place and commenting it out.
>> >>
>> >> My recommendations:
>> >>
>> >> 1. Set both t and i = 1 and try to run your loop code manually to
>> locate
>> >> the specific function providing the error.
>> >> 2. Check your data inputs for the function.  The error tells you that
>> >> some data is missing or infinite.  Perhaps a slight error in your data
>> >> generation?
>> >> 3. See if you can address the specific instance before running the full
>> >> loops, it may be multiple instances or just one.
>> >>
>> >> I hope this provides some guidance,
>> >>
>> >> Charles
>> >>
>> >>
>> >> On Thu, Jun 5, 2014 at 3:10 AM, thanoon younis <
>> >> thanoon.younis80@gmail.com> wrote:
>> >>
>> >>> Dear Dr. Charles
>> >>> i need your help to correct the winbugs code below to estimate
>> >>> parameters of SEM by using bayesian inference for two group. I have
>> this
>> >>> error"Error in eigen(Sigma, symmetric = TRUE, EISPACK = EISPACK) :
>> infinite
>> >>> or missing values in 'x'.
>> >>>
>> >>> many thanks in advance
>> >>>
>> >>> R-CODE
>> >>>
>> >>> library(MASS)      #Load the MASS package
>> >>> library(R2WinBUGS) #Load the R2WinBUGS package
>> >>> library(boa)       #Load the boa package
>> >>> library(coda)      #Load the coda package
>> >>>
>> >>> N1<-200;N2=100; P1<-10;P2<-10
>> >>>
>> >>> phi1<-matrix(NA,nrow=4,ncol=4) #The covariance matrix of xi1
>> >>> Ro1<-matrix(NA,nrow=4,ncol=4)
>> >>> yo1<-matrix(data=NA,nrow=200,ncol=10)
>> >>>
>> >>> phi2<-matrix(NA,nrow=4,ncol=4) #The covariance matrix of xi2
>> >>> Ro2<-matrix(NA,nrow=4,ncol=4)
>> >>> yo2<-matrix(data=NA,nrow=200,ncol=10)
>> >>>
>> >>> #Matrices save the Bayesian Estimates and Standard Errors
>> >>> Eu1<-matrix(data=NA,nrow=100,ncol=10)
>> >>> SEu<-matrix(data=NA,nrow=100,ncol=10)
>> >>> Elam1<-matrix(data=NA,nrow=100,ncol=6)
>> >>> SElam1<-matrix(data=NA,nrow=100,ncol=6)
>> >>> Egam1<-matrix(data=NA,nrow=100,ncol=4)
>> >>> SEgam1<-matrix(data=NA,nrow=100,ncol=4)
>> >>> Ephx1<-matrix(data=NA,nrow=100,ncol=4)
>> >>> SEphx1<-matrix(data=NA,nrow=100,ncol=4)
>> >>> Eb1<-numeric(100); SEb<-numeric(100)
>> >>> Esgd1<-numeric(100); SEsgd<-numeric(100)
>> >>> Eu2<-matrix(data=NA,nrow=100,ncol=10)
>> >>> SEu2<-matrix(data=NA,nrow=100,ncol=10)
>> >>> Elam2<-matrix(data=NA,nrow=100,ncol=6)
>> >>> SElam2<-matrix(data=NA,nrow=100,ncol=6)
>> >>> Egam2<-matrix(data=NA,nrow=100,ncol=3)
>> >>> SEgam2<-matrix(data=NA,nrow=100,ncol=3)
>> >>> Ephx2<-matrix(data=NA,nrow=100,ncol=3)
>> >>> SEphx2<-matrix(data=NA,nrow=100,ncol=3)
>> >>> Eb2<-numeric(100); SEb2<-numeric(100)
>> >>> Esgd2<-numeric(100); SEsgd2<-numeric(100)
>> >>>
>> >>>
>> >>> #Arrays save the HPD intervals
>> >>> mu.y1=array(NA, c(100,10,2))
>> >>> lam1=array(NA, c(100,6,2))
>> >>> gam1=array(NA, c(100,4,2))
>> >>> sgd1=array(NA, c(100,2))
>> >>> phx1=array(NA, c(100,4,2))
>> >>> mu.y2=array(NA, c(100,10,2))
>> >>> lam2=array(NA, c(100,6,2))
>> >>> gam2=array(NA, c(100,3,2))
>> >>> sgd2=array(NA, c(100,2))
>> >>> phx2=array(NA, c(100,3,2))
>> >>>
>> >>> DIC=numeric(100)    #DIC values
>> >>>
>> >>> #Parameters to be estimated
>> >>> parameters<-c
>> >>>
>> ("mu.y1","lam1","gam1","phi1","psi1","psd1","sgd1","phx1","mu.y2","lam2","gam2","phi2","psi2","psd2","sgd2","phx2")
>> >>>
>> >>> #Initial values for the MCMC in WinBUGS
>> >>> init1<-list(uby1=rep(0.0,10),lam1=rep(0.0,10),
>> >>>
>> >>>
>> gam1=c(1.0,1.0,1.0,1.0),psd1=1.0,phi1=matrix(data=c(1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0),ncol=4,byrow=TRUE),psi1=rep(0.0,10),
>> >>>
>> >>>
>> xi1=matrix(data=rep(0.0,200),ncol=4),xi2=matrix(data=rep(0.0,200),ncol=4))
>> >>>
>> >>>
>> >>> init2<-list(mu.y1=rep(0.0,10),lam1=rep(0.0,10),
>> >>>
>> gam1=c(1.0,1.0,1.0,1.0),psd1=1.0,phi1=matrix(data=c(1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0),ncol=4,byrow=TRUE),psi1=rep(0.0,10),xi1=matrix(data=rep
>> >>>  (0.0,200),ncol=4),xi2=matrix(data=rep(0.0,200),ncol=4))
>> >>>
>> >>>
>> >>> inits<-list(init1, init2)
>> >>>
>> >>> #Do simulation for 100 replications
>> >>> for (t in 1:100) {
>> >>>     #Generate the data for the simulation study
>> >>>     for (i in 1:N1) {
>> >>>         #Generate xi1
>> >>>         xi1<-mvrnorm(1,c(0,0,0,0),phi1, tol = 1e-6, empirical = FALSE,
>> >>> EISPACK = FALSE)
>> >>>         #Generate error term is structural equation
>> >>>         delta<-rnorm(1,0,sqrt(0.3))
>> >>>         #Generate eta1 according to the structural equation
>> >>>         eta1<-xi1[1]+xi1[2]+xi1[3]+xi1[1]*xi1[2]+delta
>> >>>         #Generate error terms in measurement equations
>> >>>         eps1<-rnorm(3,0,1)
>> >>>
>> >>>         #Generate theta according to measurement equations
>> >>>
>> >>>
>> >>>         Y1[i,1]=Xi1[i,1]+eps1[1]
>> >>>         Y1[i,2]=0.8*Xi1[i,1]+eps1[2]
>> >>>         Y1[i,3]=0.8*Xi1[i,1]+eps1[3]
>> >>>         Y1[i,4]=0.8*Xi1[i,1]+eps1[4]
>> >>>         Y1[i,5]=Xi1[i,2]+eps1[5]
>> >>>         Y1[i,6]=0.8*Xi1[i,2]+eps1[6]
>> >>>         Y1[i,7]=Xi1[i,3]+eps1[7]
>> >>>         Y1[i,8]=Xi1[i,2]+eps1[8]
>> >>>         Y1[i,9]=Eta1[i]+eps1[9]
>> >>>         Y1[i,10]=0.8*Eta1[i]+eps1[10]
>> >>>     }
>> >>>
>> >>>         #transform theta to orinal variables
>> >>>         for (j in 1:10) { if (Y1[j]>0) yo1[i,j]<-1 else yo1[i,j]<-0 }
>> >>>
>> >>>
>> >>>     #Input data set for WinBUGS
>> >>>     data<-list(N1=200,N2=200,P=10,R=Ro,z=yo1)
>> >>>
>> >>>     #Call WinBUGS
>> >>>     model<-bugs(data,inits,parameters,model.file="D:/Run/model.txt",
>> >>>     n.chains=2,n.iter=5000,n.burnin=1,n.thin=1,DIC=True,
>> >>>     bugs.directory="c:/Program Files/WinBUGS14/",
>> >>>     working.directory="D:/Run/")
>> >>>
>> >>>     #Save Bayesian Estimates
>> >>>     Eu1[t,]<-model$mean$uby; Elam1[t,]<-model$mean$lam;
>> >>>     Egam1[t,]<-model$mean$gam
>> >>>     Ephx1[t,1]<-model$mean$phx1[1,1]; Ephx1[t,2]<-model$mean$phx1[1,2]
>> >>>     Ephx1[t,3]<-model$mean$phx1[2,2];
>> >>>     Esgd1[t]<-model$mean$sgd
>> >>>
>> >>>     #Save Standard Errors
>> >>>     SEu1[t,]<-model$sd$uby1; SElam1[t,]<-model$sd$lam;
>> >>>     SEgam1[t,]<-model$sd$gam1
>> >>>     SEphx1[t,1]<-model$sd$phx1[1,1]; SEphx1[t,2]<-model$sd$phx1[1,2]
>> >>>     SEphx1[t,3]<-model$sd$phx1[2,2]; SEb1[t]<-model$sd$ubeta1
>> >>>     SEsgd1[t]<-model$sd$sgd
>> >>>
>> >>>     #Save HPD intervals
>> >>>     for (i in 1:10) {
>> >>>         temp=model$sims.array[,1,i];
>> >>>         uby[t,i,]=boa.hpd(temp,0.05)
>> >>>     }
>> >>>     temp=model$sims.array[,1,10]; ubeta[t,]=boa.hpd(temp,0.05)
>> >>>     for (i in 1:6) {
>> >>>         temp=model$sims.array[,1,10+i];
>> >>>         lam[t,i,]=boa.hpd(temp,0.05)
>> >>>     }
>> >>>     for (i in 1:3) {
>> >>>         temp=model$sims.array[,1,16+i];
>> >>>         gam[t,i,]=boa.hpd(temp,0.05)
>> >>>     }
>> >>>     temp=model$sims.array[,1,20]; sgd[t,]=boa.hpd(temp,0.05)
>> >>>     temp=model$sims.array[,1,21]; phx[t,1,]=boa.hpd(temp,0.05)
>> >>>     temp=model$sims.array[,1,22]; phx[t,2,]=boa.hpd(temp,0.05)
>> >>>     temp=model$sims.array[,1,24]; phx[t,3,]=boa.hpd(temp,0.05)
>> >>>
>> >>>     #Save DIC value
>> >>>     DIC[t]=model#DIC
>> >>> }   #end
>> >>>
>> >>>
>> >>>
>> >>
>> >>
>> >> --
>> >> Dr. Charles Determan, PhD
>> >> Integrated Biosciences
>> >> University of Minnesota
>> >>
>> >
>> >
>>
>>
>> --
>> Dr. Charles Determan, PhD
>> Integrated Biosciences
>>
>>         [[alternative HTML version deleted]]
>>
>> ______________________________________________
>> R-help@r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>
>


-- 
Dr. Charles Determan, PhD
Integrated Biosciences

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