search for: rngseed

...ding the dataset from the internet (it is not too big): library(norm) df<-download.file("http://www.tariqkhan.org/R/DataFromExcel.csv", "C:/Program Files/R/d.csv") mat<-as.matrix(read.table("C:/Program Files/R/d.csv", sep = ",")) s<-prelim.norm(mat) rngseed(1234567) thetahat<-em.norm(s, maxits = 1000, criterion = 0.0035) Iterations of EM: 1...2...3........348...349...Error: NA/NaN/Inf in foreign function call (arg 2) Someone else on the list found that using scale() helped with em.norm, but for me it only increased the number of iterations before...

Hello all I'm running da.norm function in R for climate data rngseed(1234567) theta1=da.norm(mydata, thetahat, steps=1000,showits=T) param1=getparam.norm(mydata,theta1) As I understand the 1000 steps represent the markov chain values. Is there a way to plot them? Something like plot(1:1000, param1$mu[]). I just can't find a way to extract them out of my theta1...

...! CODE: ## Set up the situation: Data<-read.csv("MyData.csv") X<-Data$X; Y<-Data$Y ##(If you want to try it, set your own data here) Raw<-cbind(X,Y) library(norm) ## Initialise stuff s<-prelim.norm(Raw) t0<-em.norm(s) ########################## ## Set the Random Seed rngseed(31425) ## Do the first imputation: t <- da.norm(s,t0,steps=20) Imp <- imp.norm(s,t, Raw) X.Imp <- Imp[,1]; Y.Imp<-Imp[,2] ## Now do the rest, and accumulate lists of the results ## Est.Imp = list of estimated coeffs ## SE.Imp = list of SEs of estimated coeffs: Est.Imp <- li...

...t V1 V2 V3 V4 ... V16 V17 1 1 1 2 6 18 18 2 1 1 1 NA 14 17 3 1 1 2 1 16 14 .... 199 2 1 NA 7 19 18 200 2 1 3 2 14 17 > EntPrelim<-prelim.mix(as.matrix(Ent),9) > EntEM<-em.mix(EntPrelim,maxits=500) > rngseed(1234567) > EntDA<-da.mix(EntPrelim, EntEM, steps=100, showits=TRUE) Steps of data Augmentation: 1... Error in da.mix(EntPrelim, EntEM, steps=100; showits=TRUE): Improper posterior--empty cells If you know what is the matter, please help us.

...ymis<-y ymis[floor(runif(10,1,n))]<-NA wmis<-w wmis[floor(runif(10,1,n))]<-NA dat<-as.data.frame(cbind(wmis,ymis,x1,x2,x3,x4)) s <- prelim.mix(dat,3) # do preliminary manipulations thetahat <- em.mix(s) # ML estimate for unrestricted model rngseed(1234567) # set random number generator seed newtheta <- da.mix(s,thetahat,steps=100) # data augmentation ximp <- imp.mix(s, newtheta, dat) # impute under newtheta ################################################################ Your mix package is important part of our ongoing...

...I am using mix and I'm trying really hard to understand, but there's just this one step I don't get...perhaps someone knows the answer? Thanks! Jens My code runs: data<-read.table('http://www.courses.fas.harvard.edu/~gov2001/Data/immigrati on.dat',header=TRUE) library(mix) rngseed(12345678) # Preare data for imputation gender1<-c() gender1<-as.integer(data$gender) gender1[gender1==1]<-2 gender1[gender1==0]<-1 data$gender<-gender1 x<-cbind(data$gender,data$ipip,data$ideol,data$prtyid, data$wage1992) colnames(x)<-c("gender","ipip",...

...nite To be honest I have no idea whatsoever what that error message means, so my experiments with mice were shortlived :-) I then tried the package "norm". I got some ways with the experiment, following the help file: s <- prelim.norm(as.matrix(myDataSet)) thetahat <- em.norm(s) rngseed(1234567) theta <- da.norm(s, thetahat, steps=20, showits=TRUE) At this stage however I get the following error: Steps of Data Augmentation: 1...2...Error: NA/NaN/Inf in foreign function call (arg 2) This seems strange to me, since the whole purpose of this routine is to work with NA values. S...

...e within the minimum and maximum of the actual data? Below is the code I am using. Thanks, Anders Corr Ph.D. Candidate #DOWNLOAD DATA (61Kb) download.file("http://www.people.fas.harvard.edu/~corr/tc.csv","C:/R") #RUN NORM tc <- read.csv("tc.csv", header = TRUE) rngseed(1234567) #set random number generator seed s <- prelim.norm(tc) thetahat <- em.norm(s) #find the MLE for a starting value theta <- da.norm(s,thetahat,steps=20,showits=TRUE,return.ymis=TRUE) #take 20 steps ximp <- imp.norm(s,thetahat,tc) #impute missing data under the MLE

...ataset works well with MICE and aregImpute() and other statistics _and_ I checked the manpages and it does not seem that the calls are wrong. Thus, either it depends on the dataset (but why?) or it is maybe a bug. I appreciate every help, thanks, leo g??rtler <---snip---> library(norm) rngseed(1234) load(url("http://www.anicca-vijja.de/lg/dframe.Rdata")) # load object "dframe" dim(dframe) apply(dframe,2,function(x) sum(is.na(x))) # check how many NAs in the dataset #dframe <- subset(dframe,select=-c(alter,grpzugeh,is1,is4,is6,klassenstufe,mmit,vorai,vorap,vora...

...rror: NA/NaN/Inf in foreign function call (arg 1). For example, > s<-prelim.mix(Y,6) Error in prelim.mix(Y, 6) : NA/NaN/Inf in foreign function call (arg 1) or when I ran: MI<-vector("list",5) #<--vector of complete data after MI fit.model.mi<-vector("list",5) rngseed(1234567) #<-- set random number generator seed margins<-c(1,2) #<-- I have two categorical variables, if I had three, the margin=c(1,2,3) design<-matrix(c(1,1,1,1,0,1,0,1,0,0,1,1),ncol=3) for (i in 1:5){ cat("Doing imputation ",i,"\n") thetahat <- ecm.mix(s,margin...

...0-9 on Windows XP Professional. #Sample code: library(norm) n<-50 p<-5 prob.miss<-.5 #generate complete data x<-matrix(rnorm(n*p),nrow=n) #create missing data for (j in 1:p) {miss<-rbinom(n,1,prob.miss) for (i in 1:n){if (miss[i]==1) x[i,j]<-NA}} #create imputations seed<-1234 rngseed(seed) s <- prelim.norm(x) thetahat <- em.norm(s,showits=F) da.norm(s,thetahat,steps=1000,showits=F,return.ymis=TRUE)

...2,blood2,agem40,agem40sq,e r,pr) #<--Y has to be a matrix for mix s<-prelim.mix(Y,6) #----------------------------run multiple imputation------------------------------# MI<-vector("list",10) #<--vector of complete data after MI fit.model.mi<-vector("list",10) rngseed(1234567) #<-- set random number generator seed for (i in 1:10){ cat("Doing imputation ",i,"\n") thetahat <- em.mix(s) newtheta <- da.mix(s, thetahat, steps=2000, showits=TRUE) MI[[i]] <- imp.mix(s, newtheta) } Here is help file about mix Help files with alia...

We've run into an interesting dilemma regarding last log information and ssh 4.2p1. In 3.8, we didn't see this problem, but now has cropped up in 4.2. When a user logs in, sshd seems to call 'last' to get the last log information. 'last' then opens the /var/log/wtmp file and processes the information. On some systems, this file can be quite large, and we're seeing

...,7 @@ usage(void) static void send_rexec_state(int fd, Buffer *conf) { + int i, num_host_keys; Buffer m; debug3("%s: entering fd = %d config len %d", __func__, fd, @@ -914,6 +916,8 @@ send_rexec_state(int fd, Buffer *conf) * bignum p " * bignum q " * string rngseed (only if OpenSSL is not self-seeded) + * u_int num_host_keys + * Key host_keys num_host_keys times */ buffer_init(&m); buffer_put_cstring(&m, buffer_ptr(conf)); @@ -934,6 +938,18 @@ send_rexec_state(int fd, Buffer *conf) rexec_send_rng_seed(&m); #endif + num_host_key...