similar to: coding nesting in data for nlme example of Wafer data set.

Dear all, I am planning to use nlme library for analysis of experiments in semiconductor industry. Currently I am using "lm" but plan to move to "lme" to handle within wafer / wafer-to-wafer and lot-to-lot variation correctly. So far everything is working well, but I have a fundamentel question: NLME offers "maximum likelihood" and "restricted maximum

I have one fixed effect, sor, with two levels. I have eight lots and three wafers from each lot. I have included the data below. I would like to fit a mixed model that estimates a covariance parameter for wafer, which is nested in lot, and two covariance parameters for lot, one for each level of sor. The following command fits the model that I want, except for it estimates the correlation

This may appear too elementary to some on this list, but not to me. My apologies if this is the case. I have mastered the lme function but the nlme function has me stumped. I am attempting to fit a nonlinear mixed model with 4 levels of nesting. I am getting a cryptic error message and do not know what is wrong with the syntax of the call. This is the call: >

Hello. I am trying to fit a nonlinear mixed model involving 3 parameters. I have successfully made a self-starting function. getInitial() correctly outputs the initial estimates. I can also use the nlsList with this function to get the separate nonlinear fits by group. However, I get an error message when using the nlme function. Here is the relevent code:

My question relates to problems that I'm having matching lme and lmer examples in P&B. using Matix 0.995 In the Oxide example in p167-170 I can't get the level 2 coefficient estimates to match the fm1Oxide model in lme is data(Oxide,package="nlme") lme(Thickness~1,Oxide) which I translate in Lmer syntax to fm3Oxide<-lmer(Thickness~

Hi helpeRs, I've been working through some examples in Pinhiero & Bates( 2000) trying to understand how to translate to the new Lme4 syntax but without much luck. Below is what I think I should do, but either the answers don't come out the same or I get errors. In the Oxide problems I'm particularly interested in obtaining the levels coeficients but this options no longer seems

Hello. I am working on an analysis involving the nonlinear mixed model function (nlme) in R. The data consist of measures of carbon fixation by leaves as a function of light intensity and the parametric function (standard in this area because it has a biological interpretation) is a non-rectangular hyperbola. I cannot get the nonlinear mixed model (nlme) function to converge cleanly. I am

Hello R-Users! Does anyone know of a package to draw/analyze silicon wafer maps? Here are some examples http://www.java2s.com/Code/Java/Chart/JFreeChartWaferMapChartDemo.htm http://dp.pdf.com/site/products/wafermap/binmap.html I've google'd and searched CRAN with no luck. It seems possible for R, given the hexbin and hist2d graphs I saw at the Graph gallery.

I am having difficulty understanding the syntax of the nlme() function for nonlinear mixed models. The data frame is called Marouane.chlorophyll. The model involves a dependent variable (Absorb) and an independent variable (Ch.surf), which are both numeric variables in the data frame. The data are hierarchically grouped as Espece, Plante nested within Espece, and Feuille nested within Plante

Hi all, I tried to do a variance components using nlme, but I got the following warning mesage ##################################################### not meaningful for factors in: Ops.factor(y[revOrder], Fitted) ###################################################### Can someone point out what is the meaning of this warning message? I tried to look at Ops.factor, but I don't

Dear All; Attempting to reproduce Figure 4.15 of MEMSS (p. 171) in R using plot(Wafer, outer = ~ Wafer) yields an error: > plot(Wafer, outer = ~ Wafer) Error in order(na.last, decreasing, ...) : Argument lengths differ The plot() produces the figure without problems for all versions of Splus (4.5 to 6.2) on Windows. Noticing that the plot() differs slightly between

Hello. I am having a problem setting up a self-starting function for use in nonlinear regression (and eventually in the mixed model version). The function is a non-rectangular hyperbola - called "NRhyperbola" - which is used for fitting leaf photosynthetic rate to light intensity. It has one independent variable (Irr) and four parameters (theta, Am, alpha and Rd). I have created this

Hi I am running some linear and non-linear mixed effect models and would like to do some planned contrasts (a priori contrasts) I have looked in the help and in many forums and it seems possible to do so but don't understand how to write the function and I couldn't find an example in Pinheiro and Bates. lme {nlme} has a contrasts argument but I can't understand how to code it.

I am getting an error message in a call to nlme and cannot understand what is happening. I explain the steps below in the hope that someone can explain the error and how to correct it. STEP 1: Data set: name: marouane.data. This is a data frame whose first few lines are as follows: > marouane.data[1:13,] species plant leaf irradiance photosynthesis chlorophyll 1

All, I am having trouble with a "read.table()" function that is inside of another function. But if I call the function by itself, it works fine. Moreover, if I run the script on a Mac OS X (with the default Mac OS X version of R installed, rev 2.8), it works fine. But it does not work if I run it on windows vista (also default Windows version of R, rev. 2.8). Again, both

This concerns the "Clinical Study of Quinidine" example on page 380 of the book "Mixed-Effects Models in S and S-PLUS" by Pinheiro and Bates (2000). I have tried to reproduce the example, but get an error: > library(nlme) > fm1Quin.nlme <- nlme(conc ~ quinModel(Subject, time, conc, dose, interval, lV, lKa, lCl), + data=Quinidine, +

Paul: I may have found the issue (which is similar to your conclusion). I checked using egsingle in the mlmRev package as these individuals are strictly nested in this case: library(mlmRev) library(nlme) fm1 <- lme(math ~ year, random=~1|schoolid/childid, egsingle) fm2 <- lmer(math ~ year +(1|schoolid:childid) + (1|schoolid), egsingle) Checking the summary of both models, the output is

Hello. I am trying to determine whether I should be using ML or REML methods to estimate a linear mixed model. In the book by Pinheiro & Bates (Mixed-effects models in S and S-PLUS, page 76) they state that one difference between REML and ML is that « LME models with different fixed-effects structures fit using REML cannot be compared on the basis of their restricted likelihoods. In

Hello, I am new to non-linear growth modelling in R and I am trying to reproduce an analysis that was done (successfully) in S-Plus. I have a simple non-linear growth model, with no nesting. I have attempted to simplify the call as much as possible (by creating another grouped object, instead of using subset= and compacting the fixed and random expressions.) This is a what the grouped

Hello. Following pages 342-347 of Pinheiro & Bates, I am trying to write a self-starting nonlinear function (a non-rectagular hyperbola) to be used in nonlinear least squares regression (and eventually for a mixed model). When I use the getInitial function for my self-starting function I get the following error message: > getInitial(photo~NRhyperbola(Irr,theta,Am,alpha,Rd),dat) Error