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Hello, I cannot find the issue and it drives me crazy :( let''s simplify. I have 2 models: saving and purchase_type a *saving* corresponds to a *purchase_type* e.g. new sourcing or renegotiation a saving has exactly one purchase_type and a purchase_type has many savings. when I try to display the list of savings and their purchase type (name, not Id), i get the dreaded "You have a

Hello, I need to remove columns in a matrix. The number of columns varies from 0 to n. I can't figure out how to specify the zero case. aa <-matrix(runif(5^2),5,5) #remove column 3 aa[,-3] #remove no column aa[,-NULL] Error in -NULL : invalid argument to unary operator I know I could use ifelse, but it would complicate my model a lot. Is there a direct way to

Hello, In a dataframe, I want the index if the last non-NA data. Example: d<-data.frame(matrix(c(1,3,4,2,7,8,1,NA,2),3,3,byrow=TRUE)) gives: > d X1 X2 X3 1 1 3 4 2 2 7 8 3 1 NA 2 I want a vector that gives me 3 2 3 I know about tail and which, but I don't know how not to consider the NA e.g.: last<-tail(d,1,na.rm=TRUE) still gives me a NA

Hello, I have a particular situation where a single "wrong" observation is impacting the results of a traditional regression to the point that betas become unreliable. I need a way to calculate the most likely betas. Here's an example: set.seed(1) unknownbeta <- matrix(seq(100,500,100),25,5,byrow=TRUE) x <-matrix(runif(25*5),25) y <- rowSums(unknownbeta*x)