search for: weekno

Does lme prediction work correctly with poly() terms? In the following simulated example, the predictions are wildly off. Or am I doing something daft? Milk yield for five cows is measured weekly for 45 weeks. Yield is simulated as cubic function of weekno + random cow effect (on intercept) + residual error. I want to recover an estimate of the fixed curve. ############### library(nlme) set.seed(1) ncows <- 5; nweeks <- 45; week <- 1:nweeks mcurve <- 25 + 0.819*week - 0.0588*week^2 + 0.000686*week^3 cow.eff <- rnorm(ncows) week <-...

...gh my summary descriptives are generated outside of R (dataset is huge), I would like to produce a box-whisker plot using bxp or perhaps a function from the ggplot2 library using the precomputed summaries. My dataset currently contains 10 rows (one row per week) with the following columns: weekno (the week over which values have been summarized), minimum, 25th and 75th percentile, median, mean, and max values. Any suggestions on how I can plot this in R to produce a box- whisker plot (one box per week of data) ? I have seen http:// finzi.psych.upenn.edu/R/library/graphics/html/bxp.h...