search for: lmcall

...mula, "Error") else terms(formula, "Error", data = data) indError <- attr(Terms, "specials")$Error if(length(indError) > 1) stop(paste("There are", length(indError), "Error terms: only 1 is allowed")) lmcall <- Call <- match.call() lmcall[[1]] <- as.name("lm") lmcall$singular.ok <- TRUE # not currently used in R if(projections) qr <- lmcall$qr <- TRUE lmcall$projections <- NULL if(is.null(indError)) { ## no Error term fit <-...

...else terms(formula, "Error", data = data) > indError <- attr(Terms, "specials")$Error > if(length(indError) > 1) > stop(paste("There are", length(indError), > "Error terms: only 1 is allowed")) > lmcall <- Call <- match.call() > lmcall[[1]] <- as.name("lm") > lmcall$singular.ok <- TRUE # not currently used in R > if(projections) qr <- lmcall$qr <- TRUE > lmcall$projections <- NULL > if(is.null(indError)) { > ## n...

...l taking on each value -- I get the error "Error in model.matrix(t, data) : invalid variable type". traceback() gives: 8: model.matrix.default(mt, mf, contrasts) 7: model.matrix(mt, mf, contrasts) 6: lm(formula = n ~ z, data = t1, singular.ok = TRUE) 5: eval(expr, envir, enclos) 4: eval(lmcall, parent.frame()) 3: aov(n ~ z, data = t1) 2: summary(aov(n ~ z, data = t1)) 1: f.test.problem(nf = 3) However, if one of the levels of z is empty (which I'm checking using table), then the analysis of variance runs! (Easy to see if you use nf = 4 or even 3; it won't take long to get some...

In a previous message I was not clear enough in my querry. I have the following program: tst<- function() { x <- c(32.7,32.3,31.5,32.1,29.7,29.1,35.7,35.9,33.1, 36.0,34.2,31.2,31.8,28.0,29.2,38.2,37.8,31.9, 32.5,31.1,29.7) g <- rep(1:7,rep(3,7)) s <- rep(1:3,7) cat(" Only x and g \n") aov1(x,g) cat("\n\n Now x, g and s \n") aov1(x,g,s=s) }