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Hello I have created a graph using the following commands: <<< startBReP3O1T <- diffs$BReP3O1T - diffs$diff_BReP3O1T endBReP3O1T <- diffs$BReP3O1T x <- seq(47,89, length = 10) ymin <- min(min(startBReP3O1T), min(endBReP3O1T)) ymax <- max(max(startBReP3O1T), max(endBReP3O1T)) y <- seq(ymin, ymax, length = 10) plot(x,y, type = 'n', xlab = 'Age', ylab =

I have repeated measures data (over time) for each of 40 individuals with the number of observations per person varying greatly from 4 to 51. There are 578 measurements in total. There are no grouping variables or other covariates. I have been using the function carma in the library called growth to fit a cubic polynomial in time with AR(1) serial correlation plus measurement error. However, I

Hello Using R 2.7.0 on Windows. I am running a linear discriminant analysis as follows <<<< discrim1 <- lda(normvar~ mafmahal+ mrfmahal+ mffmahal+ bafmahal+ brfmahal+ cofmahal+ bmfmahal+ cfmahal+ fractmahal+ antmahal+ absmifmahal+ absifmahal, subset = train) prediction <- predict(discrim1, traintest1[-train,])$class >>> When I do this, I get a warning

Hello I wrote a simple program to modify a boxplot: <<< gdsbox <- function(indvar){ boxplot(indvar~gds3lev, main = paste('Boxplot of', substitute(indvar), "for GDS groups"), names = c('1', '3', '4, 5, 6')) } >>> If I attach the dataframe gdsgraph, this works fine. However, I've been warned against attach. When I tried

Dear r-help I am trying to run LDA on a training data set, and test it on another data set with the same variables. I found examples using crossvalidation, and using training and testing data sets set up with sample, but not when they are preassigned. Here is what I tried # FIRST SET UP A DATAFRAME WITH ALL THE DATA AND CREATE NEW VARIABLES traintest1 <-