search for: pedrosmarqu

Hi, I would like to know if there is an algorithm in R for testing if a data set as a normal destribution. Thank you for your time, Pedro Marques

Hi all, Since I was having several problems trying to work with a large matrix I started to use the package R.huge but I'm having the following problem > x<-FileByteMatrix("covtype.data",nrow=581012,ncol=55) Error: cannot allocate vector of size 770.8 Mb In addition: Warning messages: 1: Reached total allocation of 447Mb: see help(memory.size) in: readChar(con = con, nchar =

Hi all, I'm trying to plot my daily time series, with 3650 observations( 10 years), with boxplot but I want 12 boxes, one for each month, can anyone help me doing that. Best regards

Hi, I would like to know if there is any algorithm in R for transforming Binary data sets. I want something like taking all the zeros and giving them some negative value, for example -5, and taking all ones and giving them some positive value, if it had been given -5 for zeros it would be 5 for all ones. Thank you for your time, Pedro Marques

Hi, I'm working with a numeric matrix with 55columns and 581012 rows and I'm having problems in allocation of memory using some of the functions in R: for example lda, rda (library MASS), princomp(package mva) and mvnorm.etest (energy package). I've read tips to use less memory in help(read.table) and managed to use some of this functions, but haven't been able to work with

Hi, I'm doing kolmogorv-smirnov test but I don't know what conclusions to take, I want to know if my data has a normal distribution: > ks.test(dados1,"pnorm") One-sample Kolmogorov-Smirnov test data: dados1 D = 0.972, p-value < 2.2e-16 alternative hypothesis: two-sided Warning message: cannot compute correct p-values with ties in: ks.test(dados1,

Hi all, I'm having this error, since I'm working with a data matrix I don't understand what's happening; I've tried several ways to solve this, even working with sparse matrix, but nothing seems to solve it, I've also tried svm (with a simple matrix 3*3 and still got the same error. > dados<-read.table("b.txt",sep="",nrows=30000) >

Hi all, I'm working with some data: 54 variables and a column of classes, each observation as one of a possible seven different classes: > var.can3<-lda(x=dados[,c(1:28,30:54)],grouping=dados[,55],CV=TRUE) Warning message: In lda.default(x, grouping, ...) : variables are collinear > summary(var.can3) Length Class Mode class 30000 factor numeric ### why?? I

Hi all, Can anyone clear my doubts about what conclusions to take with the following what puts of some time series tests: > adf.test(melbmax) Augmented Dickey-Fuller Test data: melbmax Dickey-Fuller = -5.4075, Lag order = 15, p-value = 0.01 alternative hypothesis: stationary Warning message: p-value smaller than printed p-value in: adf.test(melbmax)

Hi all, I'm working with some data with 54 variables, 44 of them are binary, and I'm using SVM in package e1071 to carry out general classification but I don't know how to choose the best kernel for my data. I would be very grateful if someone could help me on this task. Best regards, Pedro Marques

Hi all, Sorry to be bothering again with probably an easy error to fix, but I've been trying to solve the problem and haven't been able yet to do it. So I'm doing this: > dados<-read.table("b.txt",sep="",nrows=30000) >

Hi all, I don't know how to choose the formula to use when plotting an svm model, I think I'm using the wrong one and so that is why I'm having trouble. I should be very grateful if someone could help me on this.. > dados<-read.table("b.txt",sep="",nrows=30000) >

Hi all, I'm trying to plot an svm model and I'm the following error: > plot(model, data= dados[,-1], formula=formula(dados[,2]~dados[,3]),svSymbol = 1, dataSymbol = 2, symbolPalette = rainbow(4),color.palette = terrain.colors) Error in terms.default(x) : no terms component Anyone knows how to solve this??? Best regards, Pedro Marques