Dear R-help, In the rms package, I have fitted an ols model with a variable represented as a restricted cubic spline, with the knot locations specified as a previously defined vector. When I save the model object and open it in another workspace which does not contain the vector of knot locations, I get an error message if I try to predict with that model. This also happens if only one workspace is used, but the vector of knot locations is removed:
library(rms) set.seed(1) x <- rnorm(100) y <- 1 + x + x^2 + rnorm(100) x.knots <- quantile(x, c(0.2, 0.5, 0.8)) ols1 <- ols(y ~ rcs(x, x.knots)) predict(ols1, data.frame(x = 0)) # This works rm(x.knots) predict(ols1, data.frame(x = 0)) # Gives error The first predict gives 1 0.8340293 while the second predict gives Error in rcs(x, x.knots) : object 'x.knots' not found The same error happens if x.knots is simply defined as a vector like c(-1, 0, 1) (i.e. not using quantile). Is this the intended behaviour? The requirement that x.knots be in the workspace seems strange, given that the knot locations are stored in ols1$Design$parms. Thanks for any help you can give. Mark Seeto National Acoustic Laboratories, Australia ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.