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Hello, The quick version of my question is how can I extract a matrix instead of a vector using tapply()? I would like to be able to access both the results of tapply() and also the index variables. In case further explanation would help: I am analyzing a large (3million rows x 9 columns) spatial/temporal dataset and am attempting to calculate the number of unique years containing any data

...w us what you'd like, we can then more easily help. ctu at bigred.unl.edu wrote: > Hi, > How about using "subset"? > x1<-tapply(subset(years, length(area)>20), function(x) length(unique(x))) > > I hope this works > Chunhao > > > Quoting hesicaia <dboyce at dal.ca>: > >> >> Hello, >> The quick version of my question is how can I extract a matrix instead of >> a vector using tapply()? I would like to be able to access both the results >> of tapply() and also the index variables. >> >> In case furthe...

Hello, I'm running a multimodel analysis which involves fitting several GAM models as implemented in package mgcv. The issue I'm having is that when I try to fit my model, gam gives me the following error message: 'Error in initial.sp(w * X, S, off) : S[[2]] matrix is not +ve definite.' The strange part of this is that the error message stops my model fitting function when run

Hello, I have a question regarding estimation of the dispersion parameter (theta) for generalized linear models with the negative binomial error structure. As I understand, there are two main methods to fit glm's using the nb error structure in R: glm.nb() or glm() with the negative.binomial(theta) family. Both functions are implemented through the MASS library. Fitting the model using these

Hello all; My question is part statistical and part R. I have performed model II major axis regression in R using both the smatr() and lmodel2() packages, but neither offers an option to statistically weight my regression. I have a vector of weights which I would like to apply to each of my regression points (x vs. y), and was hoping that someone out there could provide me with some help on this

Hi all, I have a question regarding subsetting of large data frames. I have two data frames ?catches? and ?tows? and they both have the same 30 variables (columns). I would like to select rows in the data frame ?tows? where all 5 specific variables are NOT matched in ?catches. That is to say, the combination of these 5 variables is unique. One or more of the variables could be the same but the