search for: sel_col

...logarithm = TRUE, parameters = parameters, : data must be one-dimensional In addition: There were 42 warnings (use warnings() to see them) Can anyone tell me what I am doing wrong? Many thanks Lorenzo ############################ library(mclust) rm(list=ls()) #Define the training dataset sel_col <- c(1,2,4) sample_percentage <- 0.9 my_data <- read.csv("http://dl.dropbox.com/u/5685598/dataedges.csv", header=FALSE) my_data <- as.matrix(my_data) set.seed(1234) ms <- sample(seq(sample_percentage*dim(my_data)[1])) train_set <- my_data[ms,...

...ly(dslicets, wind, by=wind, max, na.rm=F) Pmult<-Pmin*Pmax #calculating product tt<-time(Pmult) for (j in 1:5) #1st nested loop { PmatWt[j,]<-Pmult[j,]*mult_col[j,] } #rolling regression analysis... for (k in 1:maxcol) #2nd nested loop { sel_col<-PmatWt[,k] if(!all(is.na(sel_col))) {Preg[,k]<-coef(lm(tt~sel_col))} } } #Code End Thanks, rcoder -- View this message in context: http://www.nabble.com/problem-with-nested-loop-for-regression-tp18792841p18792841.html Sent from the R help mailing list archive at N...

...uot;) newmat<-data.matrix(newx) # matrix of coefficients rownum=2 colnum=100 ResultMat<-matrix(NA, ncol=colnum, nrow=rownum) rownum2=45 colnum2=100 ResultMat2<-matrix(NA, ncol=colnum2, nrow=rownum2) #loop through each column in the source matrix for (i in 1:100) { sel_col<-newmat[col(newmat)==i] {ResultMat[,i]<-coef(fitdistr(sel_col,"weibull"))} xwei.shape<- ResultMat[1,i] xwei.scale<- ResultMat[2,i] curve(pweibull(x, shape=xwei.shape, scale=xwei.scale, lower.tail=TRUE, log.p = FALSE), add=TRUE, col='grey',lwd=0.5...

Hi everyone, I'm having trouble applying the Cor() function to two matrices, both of which contain NAs. I am doing the following: a<-cor(m1, m2, use="complete.obs") ... and I get the following error message: Error in cor(m1, m2, use = "complete.obs") : no complete element pairs Does anyone know how I can apply a correlation, ignoring any NAs? Thanks, rcoder --