similar to: naming datasubsets in a loop

Dear All I would need to generate differences between variates such as nam1<-nam2-nam3 in the following loop: for(i in c("13","26","38")) { for (j in c("HR","PQ","QRS","QT")){ nam1<-paste("d",j,i,sep="") nam2<-paste(j,i,sep=".")

Here is a small reproducible example: data <- structure(list(V1 = structure(1:3, .Label = c("Name1", "Name2", "Name3"), class = "factor"), V2 = structure(c(1L, 3L, 2L), .Label = c("nam1", "name-1", "name_12"), class = "factor"), V3 = structure(1:3, .Label = c("nam2", "nam_34",

Dear All, I would like to use the simprof function (clustsig package) but the available distances do not include Jaccard distance, which is the most appropriate for pres/abs community data. Here is the core of the function: > simprof function (data, num.expected = 1000, num.simulated = 999, method.cluster = "average", method.distance = "euclidean", method.transform =

Is this the solution? > d1<- as.data.frame(lapply(data,as.character),stringsAsFactors=FALSE) > str(d1) 'data.frame': 3 obs. of 5 variables: $ V1: chr "Name1" "Name2" "Name3" $ V2: chr "nam1" "name_12" "name-1" $ V3: chr "nam2" "nam_34" "name-2" $ V4: chr "nam3"

I am not really sure what the warning means but I think your underlying problem is that all your variables are factors. Did you intend the values in each variable to be character? data.frame':??? 3 obs. of? 5 variables: ?$ V1: Factor w/ 3 levels "Name1","Name2",..: 1 2 3 ?$ V2: Factor w/ 3 levels "nam1","name-1",..: 1 3 2 ?$ V3: Factor w/ 3 levels

I would like to be able to use lme to fit random effect models In which some but not all of the random effects are constrained to be independent. It seems as thought the pdMat options in lme are a promising avenue. However, none of the existing pdMat classes seem to allow what I want. As a specific example, I would like to fit a random intercept/slope mixed model to longitudinal observations in

Hi everyone,   I have got the following problem:   x1 <- rnorm(10,5,1) x2 <- runif(10,0,1) nam1 <- paste("A",1:4,sep=".") nam2 <- paste("A",6:9,sep=".") nam <- c(nam1,"A.4",nam2,"A.9") mydata <- data.frame(x1,x2) rownames(mydata) <- nam Error in `row.names<-.data.frame`(`*tmp*`, value = c("A.1",

Hi all, I am trying to compare two distance matrices with R. I would like to create a XY plot of these matrices and do some linear regression on it. But, I am a bit new to R, so i have a few questions (I searched in the documentation with no success). The first problem is loading a distance matrix into R. This matrix is the output of a the Phylip program Protdist and lookes like this: 5

Dear all, I'm trying to remove some text after the period (a decimal point) in the data frame 'hi', below. This is one step in formatting a table. So I would like e.g. "2.0" to become "2" and "5.3" to be "5.3", where the variable digordered contains the number of digits after the decimal that I would like to display, in the same order in which

Readers, For a data set: text1,23,text2,45 text1,23,text3,78 text1,23,text3,56 text1,23,text2,45 The following command was entered: datasubset<-data.frame(dataset[,3]=="text3") The result of datasubset is TRUE TRUE The required result is text1,23,text3,78 text1,23,text3,56 What is the correct command to use please? Thanks in advance.

R-help: I have a variable ("ID_list") containing about 1800 unique numbers, and a 143066x29 data frame. One of the columns ("ID") in my data frame contains a list of ids, many of which appear more than once. I'd like to find the subset of my data frame for which "ID" matches one of the numbers in "ID_list." I'm pretty sure I could write a function

Hi everyone- I have a dataset with multiple "pre" and "post" variables I want to compare. The variables are named "apple_pre" or "pre_banana" with the corresponding post variables named "apple_post" or "post_banana". The variables are in no particular order. apple_pre orange_pre orange_post pre_banana apple_post post_banana person_1

Hi When I run my script using ggplot and geom_smooth I get messages that I would like to suppress: p <- ggplot(dataSubset) p <- p + aes(x = as.Date(factor(key),format="%Y%m%d")) + geom_line() p <- p + geom_smooth(span=0.2,se=FALSE,size=0.7) The messages look like this: geom_smooth: method="auto" and size of largest group is <1000, so using loess. Use 'method

Dear R Community, I am new to R, and have a question that I suspect may be quite simple but is proving a formidable roadblock for me. I have a large data set that includes water-quality measurements collected over many 24-hour periods. The date and time of sample collection are in a combined Date/Time field in the format yyyy-mm-dd hh:mm:ss. I need to be able to subset the data for analysis of