similar to: tapply changing order of factor levels?

Hello! I have larger and a smaller data frame with 1 factor in each - it's the same factor: large.frame<-data.frame(myfactor=LETTERS[1:10]) small.frame<-data.frame(myfactor=LETTERS[c(9,7,5,3,1)]) levels(large.frame$myfactor) levels(small.frame$myfactor) table(large.frame$myfactor) table(small.frame$myfactor) myfactor has 10 levels in large.frame and 5 levels in small.frame. All 5

R factors are the natural way to represent factors -- and should be efficient since they use small integers. But in fact, for many (but not all) operations, R factors are considerably slower than integers, or even character strings. This appears to be because whenever a factor vector is subsetted, the entire levels vector is copied. For example: > i1 <- sample(1e4,1e6,replace=T) > c1

Hi folks, I am working with repeated measures data and I ran into issues where the paired t-test results did not match those obtained by employing glht() contrasts on a lme model. While the lme model itself appears to be fine, there seems to be some discrepancy with using glht() on the lme model (unless I am missing something here). I was wondering if someone could help identify the issue. On

I have a data frame with some factor columns. I want to drop the rows with rare factor values (and remove the factor values from the factors). E.g., frame$MyFactor takes values A 1,000 times, B 2,000 times, C 30 times and D 4 times. I want to remove all rows which assume rare values (<1%), i.e., C and D. i.e., frame <- frame[[! (frame$MyFactor %in% c("A","B"))]] except

Dear R help group, I am teaching myself linear mixed models with missing data since I would like to analyze a stats design with these kind of models. The textbook example is for the procedure "proc MIXED" in SAS, but I would like to know if there is an equivalent in R. This example only includes two time-measurements across subjects (a t-test "with missing values"), but I

Hello, I have a list of data with multiple elements, and each element in the list has multiple variables in it. Here's an example: ### Make the fake data dv <- c(1,3,4,2,2,3,2,5,6,3,4,4,3,5,6) subject <- factor(c("s1","s1","s1","s2","s2","s2","s3","s3","s3",

Dear All: I'd like to know how to sort and then index a vector of floats by several levels in R. For example >x<-rnorm(100) > MyLevels<-quantile(x,probs=c(0,.5,1)) > MyLevels 0% 50% 100% -2.11978442 -0.03770613 2.00186397 next i want to replace each x[i] in x by 1,2,3 or 4 depending on which quantile that x[i] falls. How do I do that in a

Hi, I'm trying to build the termstrc 1.1 package from its source on R 2.7.2 on Windows XP. However instead of building the package it just zips the entire source into a .tar.gz file. This is the first time I'm trying to build an R package from source. I installed the R toolset for Windows and set RTools as well as Perl & MinGW directories in the path. Anybody tried this out? Any file

Dear list, For a reason it would take me long to explain, I need to do something along the lines of what's shown below -- i.e., create an object from dplyr::summarise, and then evaluate it on a data frame. I know I could directly do: df %>% dplyr::summarise(x1_mean = mean(x1)) but this is not what I'm looking for. library(dplyr) df <- data.frame(x1 = rnorm(100), x2 =

Hi, I searched for this in the mailing list, but found no results. I have a large dataframe ( dim(mydata)= 1297059 16, object.size(mydata= 145280576) ) , and I want to perform some calculations which can be done by a factor's levels, say, mydata$myfactor. So what I want is to split this dataframe into nlevels(mydata$myfactor) = 80 levels. But I must do this efficiently, that is, I

Dear everybody, I have the following challenge. I have a data set with 2 subgroups, dates (days), and corresponding values (see example code below). Within each subgroup: I need to aggregate (sum) the values by week - for weeks that start on a Monday (for example, 2008-12-29 was a Monday). I find it difficult because I have missing dates in my data - so that sometimes I don't even have the

Hi, I need to export to LaTex the summary of a PCA. So: myPCA <- prcomp(myDF) mySummary <- summary(myPCA) # print(xtable(mySummary)) How can I export to LaTeX not all the summary but only the first nPCs?? Best Riccardo

I have 3 questions (below). Background: I am teaching an introductory statistics course in which we are covering (among other things) repeated measures anova. This time around teaching it, we are using R for all of our computations. We are starting by covering the univariate approach to repeated measures anova. Doing a basic repeated measures anova (univariate approach) using aov() seems

Hi ComRades, I want to make a matrix of frequencies from vectors of a continuous variable spanning different values. For example this code x<-c(runif(100,10,40),runif(100,43,55)) y<-c(runif(100,7,35),runif(100,37,50)) z<-c(runif(100,10,42),runif(100,45,52)) a<-table(ceiling(x)) b<-table(ceiling(y)) c<-table(ceiling(z)) a b c will give me three tables that start and end at

Hola: Si aún hay alguien que no está de vacaciones, igual me pueden ayudar. Quiero ajustar unos modelos: REG_LOG <- glm (low ~ X, family = "binomial", data = DATOS) Ejemplo: library(MASS) data(birthwt, package="MASS") birthwt$low <- factor(birthwt$low) birthwt$race <- factor(birthwt$smoke) REG_LOG <- glm (low ~ smoke, family =

Hi R-experts! Every once in a while I need to convert a factor to a vector of numeric values. as.numeric(myfactor) of course returns a nice numeric vector of the indexes of the levels which is usually not what I had in mind: > v <- c(25, 3.78, 16.5, 37, 109) > f <- factor(v) > f [1] 25 3.78 16.5 37 109 Levels: 3.78 16.5 25 37 109 > as.numeric(f) [1] 3 1 2 4 5 > What I

Hi, I'm trying to use the package termstrc. However I cannot figure out how to invoke helper functions like create_cashflows_matrix & create_maturities_matrix. Even when I try to invoke those with the data supplied with the package (say, corpbonds), it throws error saying "Error in as.vector(x, mode) : invalid 'mode' argument". Can anybody provide some working example

Hi, I am getting following tyoe of error while trying to configure node using ocfs2 o2cb_ctl: internal logic failure while creating node My Kernel version is 2.6.9-22.ELsmp Rpm which i use are ocfs2-2.6.9-22.ELsmp-1.0.7-1.i686.rpm ocfs2console-1.0.3-1.i386.rpm ocfs2-tools-1.0.3-1.i386.rpm after that I gave command ocfs2console Select Cluster ? Configure Nodes Click on Add and enter the Name

I apologize for my constant questions but I am new to R and trying to gain an appreciation for its capabilities. The following task is easy in Excel and I was hoping somebody could give me a quick explanation for how it can be acheived in R so I can avoid having to switch between the two applications. How do I find the Summary Statistics in one Vector of the dataframe by levels in another of the

Hi Is there any way to temporarily stop the updated_at field from being updated when a record is modified with ActiveRecord? I have a date field which is keeping track of when the record data was last checked by my application and my app manually updates it, of course when I do this the updated_at field is also touched making it fairly useless for finding out when the actual data was changed