similar to: read.table input array

Hello, applying a function to a list of variables I face the following problem: Let's say I want to compute tables for several variables. I could write a command for every single table, like bravo<-c(1,1,2,3,5,5,5,);charly<-c(7,7,4,4,2,1) table(bravo); table(charly) > table(bravo); table(charly) bravo 1 2 3 5 2 1 1 3 charly 1 2 4 7 1 1 2 2 The results are two tables with the

Hi I would like to write a script that reads a list of variable names. These variable names are some of the column headers in a data.frame. Then I want do a for-loop to execute various operations on the specified variables in the data.frame, but can't figure out how to do the necessary variable substitution. In bash (or C) I would use "$var", but there seems to be no equivalent in

Hello, I have been trying to write a small program to generate automatic plots. What I want is to draw boxplots for some variables in my data frame, contrasting with a variable called 'missing' that has value 1 if some variable in a concrete case has at least one missing value, in order to check if the cases that don't enter in my analysis are biased. The first attempt was to

Dear all. I am having ten variables (let's call the four of them as Alpha, Beta, Gamma and Delta.....) For each variable I have to print around 100 (plots). E So far I was copying paste the code below many times. pdf(file="DC_Alpha_All.pdf", width=15) # First Variable is treated as string plot_dc_for_multiple_kapas(Alpha, 4, c(5, 4), coloridx=c(24, 32)) # First Variable is

Dear R-users, I would like to calculate elasticities and sensitivities of each parameters involved in the following transition matrix: A <- matrix(c( sigma*s0*f1, sigma*s0*f2, s, v ), nrow=2, byrow=TRUE,dimnames=list(stage,stage)) The command "eigen.analysis" avaliable in package "popbio" provides sensibility matrix and elasticity matrix

We got some errors and eventually figured out that parallel::clusterExport second argument is "varlist" while in snow::clusterExport it is "list". The user had loaded parallel first, but did something else which inadvertently loaded snow, then clusterExport failed because we had "varlist" and not "list". Are these different on purpose? pj -- Paul E.

Friends I can't quite find a direct answer to this question from the lists, so here goes: I have several dataframes, 200+ columns 2000+ rows. I wish to script some operations to perform on some of the variables (columns) in the data frames not knowing what the column number is, hence have to refer by name. I have variable names in a text file "varlist". So, something like this:

Hi,I use the 'lmekin' model of the 'kinship' package of R in order to estimate heritability. I want to estimate the confidence interval of the variance coefficient and so I should use a bootstrap simulation. The pedigree file has 1386 subjects so I create a kinship matrix [1386*1386].This is the code of R I use: kfit2 <- lmekin(IT~1+AGE +(1|ID), dati1,

Hi, I want to subset a data frame if one of the variables matches any in a list. I could of course do something like this: subset(dataset, var == 1 | var == 2 | var ==3) but that's tedious. I tried varlist = c(1,2,3,4) subset(dataset, any(var == varlist)) but it doesn't work because 'any' doesn't go row-by-row and hence always returns TRUE. Is there any simple way to do this?

Hi! I'm a recent convert from Stata, so forgive my ignorance. In Stata, I can write foreach loops (example below) foreach var of varlist p1-p14 { foreach y of varlist p15-p269 { reg `var' `y' } } It's looping p1-p15, p1-p16...., p1-p269, p2-p15, p2-p16,... p2-p269,... variable pairs. How can I write something similar in R? I 'tried' understanding the

I am making the question clear. Please help. > Dear R experts > > I was using kinship package to fit mixed model with kinship matrix. > The package looks like lme4, but I could find a way to extract p-value > out of it. I need to extract is as I need to analyse large number of > variables (> 10000). > > Please help me: > > require(kinship) > > #Generating

The survexp function can fail when called from another function. The "why" of this has me baffled, however. Here is a simple test case, using a very stripped down version of survexp: survexp.test <- function(formula, data, weights, subset, na.action, rmap, times, cohort=TRUE, conditional=FALSE, ratetable=survexp.us, scale=1, npoints, se.fit,

Hi,? I'm trying to obtain a table of coefficients and confidence intervals from a logistic regression analysis in R. My code is as follows: # read in csv file datafile<-read.csv("file.csv", row.names=1) # read in the variable list varlist<-names(datafile)[66:180] models<-lapply(varlist, function(x) {glm(substitute(outcome ~ i, list(i=as.name(x))), data=datafile, family =

Hello all I have what seems like a simple question but have not been able to find an answer on the forum. I'm trying to define a function which involves regression models and a large number of covariates. I would like the function to accept any number of covariates and, ideally, I would like to be able to enter the covariates in a group (e.g. as a list) rather than individually. Is there any

Hello again I have a file from SPSS in .sav format. when I run library(foreign) cvar<-as.data.frame(read.spss("c:\\NDRI\\cvar\\data\\cvar2rev3.sav")) I get a warning Warning message: c:\NDRI\cvar\data\cvar2rev3.sav: Compression bias (0) is not the usual value of 100. The data appear to be OK, but I am concerned. (I tried searching the archives and the documenation for data

I'm attempting to pass a string argument into the function randomForest but I get an error: state <- paste(list("fruit ~", "apples+oranges+blueberries", "data=fruits.data, mtry=2, do.trace=100, na.action=na.omit, keep.forest=TRUE"), sep= " ", collapse="") model.rf <- randomForest(state) Error in if (n==0) stop ("data(x) has 0

# I'm new to R and am trying to get the hang of how it handles # dataframes & loops. If anyone can help me with some simple tasks, # I'd be much obliged. # First, i'd like to generate some random data in a dataframe # to efficiently illustrate what I'm up to. # let's say I have six variables as listed below (I really # have hundreds, but a few will illustrate the point). #

I have a data.frame with ~100 columns and I need a barplot for each column produced and saved in some directory. I am not sure it is possible - so please help me. this is my loop that does not work... vars <- list (substitute (G01_01), substitute (G01_02), substitute (G01_03), substitute (G01_04)) results <- data.frame ('Variable Name'=rep (NA, length (vars)),

Dear R users, I'm using the function coxme of the package coxme in order to build Cox models with complex random effects. Unfortunately, I sometimes get surprising estimations of the variances of the random effects. I ran models with different fixed covariates but always with the same 3 random effects defined by the argument varlist=coxmeMlist(list(mat1,mat2,mat3), rescale = F, pdcheck = F,

Dear all, I am using "coxme" function in Kinship library to fit random treatment effect nested within centre. I got 3 treatments (0,1,2) and 3 centres. I used following commands, but got an error. > ugroup=paste(rep(1:3,each=3),rep(0:2,3),sep='/') > mat1=bdsmatrix(rep(c(1,1,1,1,1,1,1,1,1),3),blocksize=rep(3,3),dimnames=list(ugroup,ugroup)) >