similar to: Shared Library Error

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),

K-means recluster data with given cluster centers Dear R user, I have several large data sets. Over time additional new data sets will be created. I want to cluster all the data in a similar/ identical way with the k-means algorithm. With the first data set I will find my cluster centers and save the cluster centers to a file [1]. This first data set is huge, it is guarantied that cluster

Hi all, I recently wrote some code to store a number of polynomial models in a list and return this list. The model is returned fine, but when I make a subsequent call to predict(), I have an error. The code for polyModel selection is listed at the end of the email. Here is an example of the error: > poly.fit <- polyModelSelection(x,y,10,F) > for (d in 1:4) { + lm.model <-

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)

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

I can do this by writing (and reading) the file according to some format of my own devising, but I'm wondering if there is a built-in way to write and then restore a matrix with not only the dimnames (which write.table/read.table can preserve) but also the names(dimnames)? Example: > M <- matrix(1:4, 2, 2) > dimnames(M) <- list(xdim=c("a", "b"),

Hello, I have a problem writing a variable to an existing file. Below is a part of my script and how it fails. I can't find "create.var.ncdf" in help Thanks for any help. Mark nc <- open.ncdf(ncname, readunlim=FALSE, write=TRUE ) missing <- 1.e+30 xdim <- nc$dim[["west_east"]] ydim <- nc$dim[["south_north"]] tdim <- nc$dim[["Time"]]

Hi everyone, I want to plot a 3D interpolation of the concentration of aquatic organisms. My goal would be to have the result represented as clouds with a density proportional to the abundance of organisms, so that I could fly (well, swim actually ;) ) through the scene and see the patches here and there. Basically, I want to do something like this: http://www.youtube.com/watch?v=27mo_Y-aU-c but

Hi all, I originally posted this to the bioconductor group, but maybe it's better suited to the r-help... I'm using som() to partition samples of gene expression data into clusters. The point is to classify control vs. experimental cases (sample clustering). The original matrix was 22283 x 8. The 8 samples have 4 controls and 4 experimentals. I transposed the matrix so that its dim

Dear all I'm a newbie regarding netcdf data. Today I realized that I maybe do not understand some basics of the netcdf. I want to create a *.nc file containing three variables for Switzerland. All data outside of the country are NAs. The third variable is calculated from the first two variables. Basically there is no problem to do that. I copy the file with the data of the first variable,

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,

Hi List, I am trying to plot a grid with an overlayed height. I have a dataframe with four variables: x,y,gridvalue,height. The dataframe has 2.5mio observations (ie grid points), I assign colors through the gridvalue using map_color_gradient thus producing: x,y,gridvalue,height,gridcol as variables of the dataframe. The grid dimensions are 1253 x 2001 (=2507253 data points). My attempts with

Hello Rprofessionals, The SOM-Obj works very well, when i normalize my data and the plot-function, too ! But i miss or didn't find the possibility , extract the information from the SOMplot "clusterSize" and "mean" for every cluster as quantitative information ( i.e. the DataFrame with an additional column which define the calculate clusters from SOM)? My intention -

Dear All, Would you please tell me how to display the sample No. on the map ? ---Below commands don't display the sample No.(from 1 to 150).--- library(som) library(klaR) iris.som3 <- som(iris[,1:4], xdim = 14,ydim = 6) library(klaR); opar<- par(xpd = NA) shardsplot(iris.som3, data.or = iris,label = TRUE) legend(3.5,14.3, col = rainbow(3), xjust =0.5, yjust = 0,legend =

Hello R users, I'm using SOM() to cluster a gene expression data set the syntax i used was dataGrid <- c(somgrid(xdim = 3, ydim = 3, topo = c("rectangular","hexagonal"))) dataClusters <- SOM(dataMatrix, grid = dataGrid) plot(dataClusters) it seems that this works just fine but the thing i can't figure out is how to determine where each data point has been

On Mon, Aug 14, 2017 at 5:29 AM, <raphael.felber at agroscope.admin.ch> wrote: Dear all > > I'm a newbie regarding netcdf data. Today I realized that I maybe do not > understand some basics of the netcdf. I want to create a *.nc file > containing three variables for Switzerland. All data outside of the country > are NAs. The third variable is calculated from the first two

Hi, in quite a few programs i can not browse the filesystem when opening a "listbox"; to be more clear: for example when i do in winword Open and the listbox appears, and i try to open the pull down menu winword just quits(without an error message in wine). In another program like "Camel join" it quits as soon as i go up to the level of "my computer" with a message

I am trying to understand how the SOM algorithm works using library(class) SOM function. I have a 1000*10 matrix and I want to be able to summarize the different types of 10-element vectors. In my real world case it is likely that most of the 1000 values are of one kind the rest of other (this is an oversimplification). Say for example: InputA<-matrix(cos(1:10),nrow=900,ncol=10,byrow=TRUE)

Hi all, I've got some functioning code that I've literally taken hours to write. My 'R' coding is getting better...it used to take days :) I know I've done a poor job of optimizing the code. In addition, I'm missing an important step and don't know where to put it. So, three questions: 1) I'd like the resulting output to be sorted on distance (ascending) and

Hi there, I would like to make a 'bumps chart' like the ones described e.g. here: http://junkcharts.typepad.com/junk_charts/bumps_chart/ Purpose: I'd like to plot the proportion of people in select countries living for less then one USD pr day in 1994 and 2004 respectively. I have already constructed a barplot - but I think a bumps chart would be better # The barplot and data