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Mangia a colori II! Keywords Population, health promotion/Public Theories, Methods & Perspectives Abstract An initiative of health-promotion to the expansion of the "instruments" able to assure the control to the population on their own level of health, to improve it through activity that partly concern to the sanitary system and partly to other sectors, with the use of internal

Dear all, I have the following problem. I have a List of time series dataframe.I'm trying to produce specific graph for each element of my list. The code is: This is my list: Lista_import<-lapply(Lista_import, function(x){ x2<-subset(x, select=c("ANNO","DICHIARANTE","PARTNER", "quota")) x2<-cast(x2, ANNO+DICHIARANTE~PARTNER) x2<-

Good day, Sometimes, sparse.model.matrix outputs a dgCMatrix which has column names consisting of factor levels that were not in the original dataset. The first factor appears to be correctly transformed, but the following factors don't. For example: diamonds <- as.data.frame(ggplot2::diamonds) > colnames(sparse.model.matrix(~ . -1, diamonds)) [1] "carat"

color and clarity are ordered factors, so sparse.model.matrix is generating orthogonal-polynomial contrasts (see ?contr.poly). This is by design ... what are you trying to do? Are you interested in fac2sparse? On 18-02-07 11:00 PM, Dario Strbenac wrote: > Good day, > > Sometimes, sparse.model.matrix outputs a dgCMatrix which has column names consisting of factor levels that were not