similar to: collapsing plot lines

All, I'm trying to create an augPred plot in the nlme library, similar to the plot on p.43 of Pinheiro & Bates (Mixed Effects Models in S and S-Plus) for their Pixel data. My data structure is the same as the example but I still get the error msg below. > comp.adj.UKV <- groupedData(adj.UKV ~ Time | Patient_no/Lisinopril, data = comp.adj.UKV.frm, order.groups = F) >

All, I'd like to plot the main relationship of a grouped data object for all levels of a factor in a single panel. The sample code below creates a separate panel for each level of the factor. I realize that this could be done in other ways, but I'd like to do it via plotting the grouped data object. thanks! dave z = rnorm(18, mean=0, sd=1) x = rep(1:6, 3) y =

All, In the function below I have 24 individuals and 6 calculations per individual. The 6 calculations are collected each time in a 1:24 loop when calculating "delta". I'd like to collect all 144 = 24*6 calculations in one vector ("delta.patient.comb"). The function works as is via indexing, but is there an easier way to collect the measurements via appendinng the 6

sent this to the list yesterday but didn't see it listed in the daily summary ... apologies if you receive it twice ... ________________________________ From: Afshartous, David Sent: Tuesday, June 27, 2006 10:02 AM To: 'r-help@stat.math.ethz.ch' Subject: sapply question All: I'm trying to use sapply to break up data within another function. (tapply doens't seem to work

All, When saving plots to a pdf file via the pdf function, I would like to be able to automatically expand the graphics device to achieve the same result as when one does this manually (e.g., clicking the green expand button on the upper left of the graph on Mac OS). Consider simple example below: library("lattice") foo.frm = data.frame(Subject = rep(c(1:4), each = 9), Y =

All, I'm having problems w/ a simple attempt to subset an xyplot. The first plot below is a plot of y versus x for certain values of a third categorical variable z. Now I'd like to further restrict this to certain values of variable y. Neither of the two attempts below work. Any suggestions much appreciated. (note: I don't want to merely use ylim since I have a loess plot and I

All, How does one replace plot symbols with say subject IDs when using xyplot? Or superimpose them next to plot symbols? I searched the archives under various key words but haven't had much. Any suggestions or links much appreciated. Sample code below. David junk.frm = data.frame(ID = rep(1:16, each = 2), x, y, z = rep(c("D", "P"), 16)) y = c( 0.4, 0.6, -0.1,

All, When I take a subset of a factor the reduced factor still maintains all the original levels of the factor when say forming the key in a plot. The data is correct, but the variable still "remembers" the original levels. See below for reproducible code. Does anyone know how to fix this? cheers, dave fact = as.factor(c(rep("A", 3),rep("B", 3), rep("C",

All, Simple question but I don't seem to be able to find the answer in the documentation: When using "plot" within a loop, is there any way to supply the argument to "main" dynamically, i.e., so that the title is Patient k below as the loop cycles through each value of k? plot(x,y, xlim=c(0,250), ylim=c(0,1000), xlab="gamma", ylab="r1",

All, Is there an efficient way to apply say "mean" or "median" to a dataframe according to say all combinations of two variables in the dataframe? Below is a simple example and the outline of a "manual" solution that will work but is not very efficient (could also generalize this to a function). Searched the archives and docs but didn't see anything close to

All, I have a repeated measures data frame and was wondering if the covariance matrix can be calculated via some created indexing or built-in R function. Specifically, say there are 3 variables, where potassium concentration is measured 6 times on each patient. Patient number (discrete) Time (1 to 6, discrete) Potassium (continuous variable) I want the covariance/correlation matrix for the

Hello all, I have matrices V.i of dimension n.i x n.i, where i = 1, ..., J, and the sum of n.i equals N. (and n.i ! = n.j) goal: create one large matrix V, where V has matrices V.i on diagonal. I create each matrix V.i in a for loop (1 to J), so each time I'd like to augment V with the most recently calculated V.i, such that I'll have V after the final iteration of the for loop.

Hello all, X is a list of 20 lists, and each individual list has 65 elements. Y is a list of 65 elements. WANT: subtract Y from each of the 20 lists in X. Here's what I tried and the error messages: > X - rep(Y, 20) Error in X - rep(Y 20) : non-numeric argument to binary operator I tried several methods w/o success. Any suggestions kindly appreciated. Thanks, Dave ps - please copy

I am encountering difficulty with NextMethod in 0.50-a4. We created a class of groupedData objects which are data.frames with additional attributes. The most important attribute is a formula describing roles of some of the variables in the experimental design. The class of such objects ends in "groupedData", "data.frame". The print method for the groupedData class simply

All, Is there one liner way to obtain the max per observation for two vectors? I looked at apply and lapply but it seems that groundwork would have to be done before applying either of those. The code below does it but seems like overkill. Thanks! Dave x = rnorm(10) y = rnorm(10) ind = which(x < y) z = x z[ind] <- y[ind] ## z now contains the max's

Hi, I'm trying to plot a grouped data object for modelling maximum branch size by distance from stem apex: >MAXBRD.group <- groupedData(MAXBRD ~ Dtop | Type/Site/Tree, inner=~Status, data=MAXBRD.data). The following code produces a plot of MAXBRD ~ Dtop for each site type: >plot(MAXBRD.group, collapse=1, display=1, aspect=1.2, pch=20, inner=~1, main="MAXBRD with

Dear R-help, I am trying to create groupedData objects using the nlme library. I'm missing something basic, I know: Here is the first example in ch.1 of Pinheiro & Bates (2000): library(nlme) x2=Rail$travel;x1=Rail$Rail;eg1=data.frame(x1,x2);eg1gd=Rail print(eg1gd) x11();print(plot(eg1gd)) femodel=lm(x2~x1-1,data=eg1gd) print(femodel$coefficients) Result: x12 x15 x11

I'm trying to write a function that has a dataframe as an argument. Within the function, I call groupedData to create a grouped-data object from the dataframe argument. However, the groupedData function doesn't seem to see the data. I'm guessing it's getting the argument name rather than its value, but I'm not positive. My system: R 1.3.1 on WinNT 4.0 (Pentium II), nlme

Hello I am trying to fit a REML to some soil mineral data which has been collected over the time period 1999 - 2004. I want to know if the 19 different treatments imposed, differ in terms of their soil mineral content. A tree model of the data has shown differences between the treatments can be attributed to the Magnesium, Potassium and organic matter content of the soil, with Magnesium being the

Hi All. I'm trying to run nlsList an getting an error that makes no sense to me. I have accuracy and reaction time data over many trials for each person (id) When I use nlsList code that is virtually identical to the example in the doc file I get the following error. I've tried everything I could think of and can't get around it. Any ideas what I'm doing wrong? **************