search for: nclust

I want use survfit() and basehaz() inside a function, but it doesn't work. Could you take a look at this problem. Thanks for your help. Following is my codes: library(survival) n <- 50 # total sample size nclust <- 5 # number of clusters clusters <- rep(1:nclust,each=n/nclust) beta0 <- c(1,2) set.seed(13) #generate phmm data set Z <- cbind(Z1=sample(0:1,n,replace=TRUE), Z2=sample(0:1,n,replace=TRUE), Z3=sample(0:1,n,replace=TRUE)) b <- cbind(rep(rnorm(nclust),each=n/nclust),re...

Hi! I just started to use R recently, and would like to ask a help about automating the job. I need to use "kmeans" function with my own 300 data files, and wonder if it's possible to do it automatically. For example, > library (mva) > mydata <- read.table ("data1") > cl <- kmeans(mydata, 5, 20) and I just need to save "cl" info (i.e. the center

..._patterns_file')) print(is.loaded('merge_xtabs_patterns_file_')) .Fortran('merge_xtabs_patterns_file_',ydim[1],ydim[2],x=as.integer(as.matrix(y)),na=as.integer(c), maxD=as.integer(maxD),lrowmem=length(rowmem),rowmem=as.integer(rowmem), sequential=as.integer(Sequential),nclust=as.integer(nclust)) The corresponding output: [1] FALSE [1] TRUE Error in .Fortran("merge_xtabs_patterns_file_", ydim[1], ydim[2], x = as.integer(as.matrix(y)), : Fortran symbol name "merge_xtabs_patterns_file_" not in load table Why is it that I get a TRUE for is.l...

...s Peter 1: R code to find cluster center and save them to file #---INITIAL CLUSTERING TO FIND CLUSTER CENTERS # LOAD LIB library(cluster) # LOAD DATA data_unclean <- read.table("dataset1.dat") data.matrix<-as.matrix(data_unclean,"any") # CLUSTER Nclust <- 100 # amount cluster centers Imax <- 200 # amount of iteration for convergence of clustering set.seed(100) # set seed of random nr generator init <- sample(dim(data.matrix)[1], Nclust) # this is the initial Nclust prototypes km <- kmeans(data.matrix, centers=data.matrix[i...

Hi there, I want to generate a random point pattern using the Neyman-Scott cluster process using spatstat package in R. After running the following procedures, why i can not see any figures? > nclust <- function(x0, y0, radius, n) {return(runifdisc(n, radius, x0, y0))} > nclust function(x0, y0, radius, n) {return(runifdisc(n, radius, x0, y0))} > X <- rNeymanScott(10, 0.2, nclust, radius=0.2, n=5) > X planar point pattern: 67 points window: rectangle = [ 0 , 1 ] x [ 0 , 1 ] >...

...ge "didivsion by zero in ReadFATSuperblock. I was able to track the problem down to the following lines in volume.c (starting from line 502) nsect -= GETWORD(buff, 0x0e) + buff[0x10] * sz + (GETWORD(buff, 0x11) * 32 + (GETWORD(buff, 0x0b) - 1)) / GETWORD(buff, 0x0b); nclust = nsect / buff[0x0d]; when i change these into this: nsect -= GETWORD(buff, 0x0e) + buff[0x10] * sz + (GETWORD(buff, 0x11) * 32 + (GETWORD(buff, 0x0b) - 1)) / (GETWORD(buff, 0x0b)-1); nclust = nsect / (buff[0x0d]+1); i can (obviuosly) avoid the division by zero and everyth...

This is the general outline of my code:: main(argc,argv){ ... Rf_initEmbeddedR(argc,argv); ... Test_tryEval("source(test.r)"); ... } ############# # test.r ############# ... dyn.load("toload.so") tmp <-matrix(data=1,nrow=narray*2,ncol=nclust) .Call("Init",tmp,...) while(...) { criteria <-feval(tmp) if (criteria < criteria.min) tmp.last <- tmp else tmp <- tmp.last ... .Call("replace",tmp,...) } #################################### When I try to recover tmp tmp...

...E) > imagedat Red Green Blue 0_0 5 7 8 1_0 5 5 18 2_0 7 8 49 3_0 22 8 76 4_0 54 10 67 5_0 50 9 28 6_0 18 10 15 7_0 9 7 6 8_0 2 5 7 ... I cluster using > cl <- kmeans(imagedat, nclust, maxsteps) > cl $cluster [1] 1 1 9 8 2 9 1 1 1 1 1 1 1 1 1 8 8 8 8 4 [25] 9 9 8 8 8 2 2 9 1 1 9 9 7 10 10 10 10 10 10 10 10 ... $centers Red Green Blue 1 9.940421 7.744428 11.11652 2 85.198120 18.363348 68.10173 3 109....