search for: datamat

...ow chooses (and uses) the spruce parameter set for the whole data object (because there is spruce on the first row?). Could someone please give a hint on what's wrong. Thanks! Sincerely, Tord relev.kols$vol<- st?volfunk(relev.kols, tradhogst = "trad") st?volfunk<- function(datamat, tradhogst=c("trad", "h?gst")) { # first pick out correct parameter sets. They depend on tree species # if tree speciec is bjork (birch) -> choose bjork.formh?jd.pars # and bjork.h?jd.pars as pars1 and pars2, respective...

...questions posted over the years about loops but I'm afraid that I'm still stuck. I am using Windows XP and R 2.9.2. I am generating some data using the multivariate normal distribution (within the 'mnormt' package). [The numerical values of sanad and covmat are not important.] > datamat <- rmnorm(n=1500,mean=c(mean(sanad[,1]),mean(sanad[,2]),mean(sanad[,3])),varcov=covmat) The middle column of 'datamat' is simulated data for age. Obviously some of the simulated values are not going to be sensible. Therefore I'd like to set up a function that looks at each row of...

...he GMM estimates for CAPM (REGRESSION) for 36 stocks each have 180 observations,however it only gives me one output rather than 36. In SAS i would just put in a *By statement*. I have a variable TICKER that categorize them into 36 groups. *How can I obtain all 36 output instead of just one.* ** DataMat<-read.table(file="C://Users//ssenriqu//Dropbox//Work//Risk//data//CRSP//CRPS 2 original1.csv",sep=",",dec=".",header=TRUE) require(gmm) Returns <- DataMat[1:6480,"Returns"] VWRET <- DataMat[1:6480,"VWRET"] RF <- DataMat[1:6480,"RF&q...

Dear R-helpers, I am using a vrtest on time series data. My commands are as follows; read.table("B.txt",sep="\t",fill=TRUE, na.strings = "NA") require(vrtest) rm(list=ls(all=TRUE)) datamat <- read.table("B.txt",sep="\t",fill=TRUE, na.strings = "NA") column <- 1 nob <- nrow(datamat) y <- log(datamat[2:nob,column])-log(datamat[1:(nob-1),column]) After, the use of last command, I get the following message; in Math.factor(c(37L, 36L, 42L...

...0.13769743 0.09924456 0.08767253 [17,] 0.20091098 0.09847140 0.14685682 0.16175769 0.18205527 0.13926859 [18,] 0.11707101 0.13492758 0.07762873 0.13414458 0.11760926 0.13963532 As you can see, values in row [15,] and columns [,3] to [,5] are very similar. To produce a vertical design matrix use: datamat<-as.data.frame(test) datamat<-stack(datamat) datamat$subject<-as.factor(rep(c(1:18),times=6)) datamat$A<-as.factor(rep(c(1:3),each=18,times=2)) datamat$B<-as.factor(rep(c("one","two"),each=54)) Then fitting the model: fm.datamat<-lme(values~A*B,data=data...

...* Each case must be identified by a strata variable (id) * Each duplicate must be identified by a variable indexing the choices (newy) * A dichotomous variable must indicate which duplicate corresponds with the respondent's choice (didep) I've done this as follows: mclgen <- function (datamat,catvar) { ncat <- nlevels(catvar) id<-1:length(catvar) datamat<-cbind(id,datamat) perschoice <-NULL for (i in 1:ncat) { perschoice<-rbind(perschoice,datamat) } perschoice<-perschoice[sort.list(perschoice$id),] perschoice$newy<-gl(ncat,1,length=nrow(perschoice)) dep&l...

...ues are not what I am expecting. I want to use the Cochran Armitage trend test to get the p-values. num.reps=10 num.vars=1000 pi0 = 80 num.subjects = 100 #Create list control list.control and list.treatment #Minor alleles will be from (0.10, 0.30) #num.subjects is the number of subjects in each datamat = matrix(0,num.vars,3) list.treat <- vector("list", 1) # create list for (i in 1: num.reps) { list.treat[[i]] <- matrix(0, nrow = num.vars, ncol=3) } for ( k in 1: num.reps) { minor.allele.prop = runif(num.vars, 0.10, 0.30) ################################### ##### Generating und...

Dear all, I am trying to make a barplot with clustered pairs of bars, using class=numeric data and the following command: barplot(c(bline_precip[10,9], bline_runoff[10,9], cccma_precip[10,9], cccma_runoff[10,9], csiro_precip[10,9], csiro_runoff[10,9], ipsl_precip[10,9], ipsl_runoff[10,9], mpi_precip[10,9], mpi_runoff[10,9], ncar_precip[10,9], ncar_runoff[10,9], ukmo_precip[10,9],

...--------------------------------------------------------------------------- library(mvtnorm); s12<-c(1:1000); var21<-lapply(s12,function(x){ rs<-rmvt(10, sigma=diag(8), df=1); my<-mean(rs); sy<-sqrt(var(rs)) return(cbind(my,sy)) }); data1<-do.call(rbind,var21); dataMat<-data.frame(data1); W<-dataMat$my; hist(W,breaks=20,probability=T) ----------------------------------------------------------------------------------- Thanks. Shant [[alternative HTML version deleted]]

...blem is that when PercentsMat is called from within a loop in SummaryMat, where list names are indexed, the rows in the generated matrix are labeled with the index name rather than its value. That is, for example, I'm ending up with ri, ri, ri rather than r1, r2, r3. SummaryMat <- function(datamat, numclusts, runs, fzmeasure) for( j in numclusts ) for( i in 1:runs ) { k = k+1 . . . sepclusters[k] = list( ClusterSep(clusters[[k]]) ) # separate data into individual clusters names(sepclust...

...ne else's code for other purposes. # Modified VAR simulation function jigged up from the predict function of vars package simVARpath<-function(object, n.ahead, mult = 1) { K <- object$K p <- object$p obs <- object$obs type <- object$type data.all <- object$datamat ynames <- colnames(object$y) n.ahead <- as.integer(n.ahead) Z <- object$datamat[, -c(1:K)] B <- Bcoef(object) if (type == "const") { Zdet <- matrix(rep(1, n.ahead), nrow = n.ahead, ncol = 1) colnames(Zdet) <- "const" }...

Dear All, I've successfully import my synteny data to R by using scan command. Below show my results. My major problem with my data is how am i going to combine the column names with the data( splt) where i have tried on cbind but a warning message occur. I have realized that the splt data only have 5 column instead of 6. Please help me with this!! I want my data to be a numerical

I am using read.csv to read a CSV file (produced by saving an Excel file as a CSV file). The columns containing dates are being read as factors. Because of this, I can not compute follow-up time, i.e. Followup<-postDate-preDate. I would appreciate any suggestion that would help me read the dates as dates and thus allow me to calculate follow-up time. Thanks John John Sorkin M.D., Ph.D. Chief,

...rmat=flowed; charset="US-ASCII" > > I have the code below but the p-values are not what I am expecting. I want > to use the Cochran Armitage trend test to get the p-values. What do you expect? Depending on the genetic model, you may not see HWE in the "cases". > datamat[h,] <- t(rmultinom(1, size=c(10, 40, 50), prob=c(0.33, 0.33, 0.34))) "size" should be the total size ie 100. -- | David Duffy (MBBS PhD) ,-_|\ | email: davidD at qimr.edu.au ph: INT+61+7+3362-0217 fax: -0101 / * | Epidemiology Unit, Quee...