similar to: Model parameterization / Factor Levels

Dear all, I am using the function 'D' in the 'stats' package to perform symbolic derivation. This works very well and it is much faster than e.g. Mathematica (at least for my purposes). First, I would like to thank the development team for this excellent function. However, I run into trouble in some cases, particularly when I am to do some operations on long expressions

I am working on a nlme model that has multiple fixed effects (linear and nonlinear) with a nonlinear (asymptotic) random effect. asymporig<-function(x,th1,th2)th1*(1-exp(-exp(th2)*x)) asymporigb<-function(x,th1b,th2b)th1b*(1-exp(-exp(th2b)*x)) mod.vol.nlme<-nlme(fa20~(ah*habdiv+ads*ds+ads2*ds2+at*trout)+asymporig(da.p,th1,th2)+ asymporigb(vol,th1b,th2b),

I am examining the following nlme model. asymporig<-function(x,th1,th2)th1*(1-exp(-exp(th2)*x)) mod1<-nlme(fa20~(ah*habdiv+ad*log(d)+ads*ds+ads2*ds2+at*trout)+asymporig(da.p,th1,th2), fixed=ah+ad+ads+ads2+at+th1+th2~1, random=th1+th2~1, start=c(ah=.9124,ad=.9252,ads=.5,ads2=-.1,at=-1,th1=2.842,th2=-6.917), data=pca1.grouped) However, the two random effects (th1 and th2)

Can some kind person point out my error here? I'm trying to set up a grid for a countour plot of a likelihood function. > u <- rnorm(20,9.5,2.5) > # sample of size 20 from N(9.5,2.5^2) > loglik <- function(th1,th2) { + n <- length(u) + -(n/2)*log(2*pi*th2^2)-0.5*sum((u-th1)^2/th2^2) + } > x <- seq(4.5,14.5,len=50) > y <- seq(0.5,6,len=50) > f <-

How to use "contour" function? I type "contour(th1,th2,SumofSquares,levels=c(seq(1000,4000,200)))" But I didn't see contour in the plot, I guess it is because my data is so big that contour is out of range. Does anybody know how to fix this problem? here th1 is a 1x101 array(158741.8-298529.6) th2 is another 1X101 array(-0.0058352269-0.2093140935) SumofSquares is a

Hi: I'm trying to estimate a latent variable model in mnl discrete choice framework using R. I need to do first a uni dimensional integral within each observation (row) in the database and then sum over observations. I'm stacked in the point shown below. Apparently I have a dimensionality problem in the definition of the integral. Maybe it does not identify that what I need is only one

Hi: I'm trying to estimate a model which involves the estimation of double integrals, so I'm using adapt procedure. I need to calculate the integrals trough my 2000 size database, so I do it using a loop. My code correctly estimates the integral for the first row, but for the second R crashes. I tried changing the order of the data but the result is the same so I guess there is something

Dear All, I am attempting to use forward and/or backward selection to determine the best model for the variables I have. Unfortunately, because I am dealing with patients and every patient is receiving treatment I need to force the variable for treatment into the model. Is there a way to do this using R? (Additionally, the model is stratified by randomisation period). I know that SAS can be

Hello, I'm trying to make a 3d plot using rgl in which the size and color of each point corresponds to certain attributes of each data point. The color attribute, let's call it X, is scaled to go from 0 to 1. The rainbow(64,start=0.7,end=0.1) palette is perfect for what I want but I don't know how to take that palette and pick a color from it based on the value of X for a given data

Hi all, I am doing nls regression of the Rogers type III equation. However I can't find good starting values and keep getting the error messages: "Missing value or an infinity produced when evaluating the model" OR "singular gradient matrix at initial parameter estimates" Is there a way to automatically check different starting values and give a list of values for each

Hi everyone! I meet one problem when embedding R in C code, when I run the the R code in one child thread , it always print error info: Error: C stack usage is too close to the limit I also try to set R_CStackLimit = (uintptr_t)-1 to disable the C stack check as the R-ext doc say, but it still does not work. it is interesting that if i put the R code in the main

Hi everyone! I meet one problem when embedding R in C code, when I run the the R code in one child thread , it always print error info: Error: C stack usage is too close to the limit I also try to set R_CStackLimit = (uintptr_t)-1 to disable the C stack check as the R-ext doc say, but it still does not work. it is interesting that if i put the R code in the main

Hi everyone! I meet one problem when embedding R in C code, when I run the the R code in one child thread , it always print error info: Error: C stack usage is too close to the limit I also try to set R_CStackLimit = (uintptr_t)-1 to disable the C stack check as the R-exts doc say, but it still does not work, the error info still exist. Besides it is interesting that if i

Hello R people, i'm trying to implement the Partial Least Squares algorithm called SAMPLS from "J.Comp-Aided Molecular Design", 7 (1993), 587-619. It's faster than the classical PLS algorithm for fat matrix (m>>n). Here's the algorithm from the article of Bush B. L. and Nachbar R.B.: X is the matrix of explanatories proprieties (m*n) , y the matrix of responses, h

I've just done a fresh lenny amd64 install, and taken the xm-debian.cfg example: http://people.debian.org/~joeyh/d-i/images/daily/netboot/xen/xm-debian.cfg and built a 32 bit lenny inside a 64 bit lenny dom0 # xm create -c xm-th2.cfg install=true install-installer=http://people.debian.org/~joeyh/d-i/images/daily/ When I try to boot the domU: # xm create -c xm-debian.cfg it

Using the small reproducible example below, I'd like to know if one can somehow use the matrix "sig" (defined below) to add a black outline (with lwd=2) to all pixels with a corresponding value of 1 in the matrix 'sig'? So for example, in the ggplot2 plot below, the pixel located at [1,3] would be outlined by a black square since the value at sig[1,3] == 1. This is my first

Dear friends: It's possible make a legend in the coplot output? My data are: "dados"<-structure (list ( Qu1 = c(1,2,3,4,5,6,7,8,3,2), Qu2 = c(3,4,5,6,7,8,9,9,6,3), Ku1 = structure (factor ( c(1,1,1,1,2,1,2,2,1,1),levels=1:2),.Label=c("Kmin","Kmax")), Ph1 = structure (factor (

Hi Eric, you can use an annotate-layer, eg ind<-which(sig>0,arr.ind = T) ggplot(m1.melted, aes(x = Month, y = Site, fill = Concentration), autoscale = FALSE, zmin = -1 * zmax1, zmax = zmax1) + geom_tile() + coord_equal() + scale_fill_gradient2(low = "darkred", mid = "white", high = "darkblue",

Dear all, I want to solve a score function by using Newton-Raphson algorithm. Is there such a fucntion in R? I know there's one called optim, but it seems only doing minimizing or maximizing. Thanks, Jimmy

Dear all, Are there any packages can estimate the partial linear model. Or any one can give me any suggestions. Many thanks in advance. Jin