similar to: sorted reshaping?

Hi all, If presented with a singular design matrix, lm drops columns to make the design matrix non-singular. What algorithm is used to select which (and how many) column(s) to drop? Particularly, given a factor, how does lm choose levels of the factor to discard? Thanks for the help. Best, Anirban [[alternative HTML version deleted]]

Hi, I have had some troubles using doubleYScale. No matter what I try, I cant manage to change the color of the y-axis in the end. I have to produce a black and white plot. There is also something I do not understand regarding fontfamilyj="serif" when using it in: strip=strip.custom() Maybe someone has a better idea for defining which line and dots belong to which y-axis when not using

Hi there, I have relative abundance data for 13 mammal species that I collected at various sites that ranged in road density. I'm trying to determine the effect of road density on animal abundance across body sizes. For most species, I have data that was collected in one year but for a few species I have two years of complete data, and would like to use both. Since I have count data, I'm

Hi there, I have a huge data set with multiple firms years and other firm characteristics. I want to run a regression on the dependent variable and other explanatory variables and calculate the residual terms by grouping the firms in same year and same industry. What I want to do is to divide my obseravtion into sub sample that contains the observation with same fiscal year(FYEAR=1990) and same

Hi, I am new to R. How can I get labels/different colours on the lines in my xy-plots. I plot "het" against "temp" conditional on "year" and "station". library(lattice) MyLines <- function(xi, yi, ...){ #Draws line in the panels while avoiding spaghetti-plots I <- order(xi) panel.lines(xi[I], yi[I], col = 1)} xyplot(het ~ temp | fstation,

Hi, I have confirmed temporal correlation problems in my data. Is there a possibility to use corCompSymm for a gamm()? I am an R-beginner. I have very short time series. There are three years and within each year, there are 10 weeks. he 10 weeks are the same every year and have not unique values, I seem not to be able to use AR-1 (I assume that I have too little data for autoregression

Dear R helpers, I would like to write a loop that makes 4 objects (called A, B, C, and D) each of which contains ten random numbers. This attempt: individuals<-c("A","B","C","D") for(i in 1:length(individuals)) { individuals[i]<-rnorm(10) } does not work because "individuals[i]" is not the proper way to extract each letter from the