similar to: Error in optim(p, fun,...)

All: I have a matrix, X, with a LARGE number of rows. Consider the following three rows of that matrix: 1 1 1 1 2 2 3 3 1 1 1 1 3 3 2 2 3 3 2 2 1 1 1 1 I wish to fit many one-way ANOVAs to some response variable using each row as a set of factors. For example, for each row above I will do something like anova(lm(Y~as.factor(X[1,]))). My problem is that in the above example, I do not want

All: I am trying to use gam in a scatterplot smoothing problem. The data being smoothed have greater 1000 observation and have multiple "humps". I can smooth the data fine using a function something like: out <- ksmooth(x,y,"normal",bandwidth=0.25) plot(x,out$y,type="l") The problem is when I try to fit the same data using gam out <-

All: Are there any functions out there for selecting all the points in a region of a plot. I envision something like the identify() function except one could circle a cloud of points (and perhaps a vector would be returned of the same length as the points plotted indicating logical membership in the circled cloud). Perhaps someone has done something with the locator() function that would

running R 1.4.1 on MAC and 1.2.2 on Linux When I use run binom.test with small N the results are a little perplexing to me >binom.test(9,20,p=0.5) gives the below plus other stuff 95 percent confidence interval: 0.2305779 0.6847219 Now: >pbiom(9,20,0.6847219) [1] 0.02499998 # i.e., lower 2.5% of distribution >pbinom(9,20,0.2305779) [1] 0.9923132 >pbinom(8,20,0.2305779)

>Date: Tue, 20 Mar 2001 15:45:52 -0800 >To: Prof Brian D Ripley <ripley at stats.ox.ac.uk> >From: Tony Long <tdlong at uci.edu> >Subject: Re: [R] error starting R 1.2.2 in Redhat 7.0 (GLIB 2.2 not >defined...) >Cc: r-help at stat.math.ethz.c >Bcc: >X-Attachments: > >Brian: > > Thanks!! I figured out how to run "up2date" (that is,

All: I just upgraded my system to Redhat 7.0, and installed the RPM for R 1.2.2. I intall R 1.2.2 using the rpm -U xxxx command. When R is invoked from some directories it starts and runs fine, from other directories I get a strange message at startup (and R exits without starting). Thus far the directory with the problem tends to contain ".data" files from the previous version

All: I am attempting to allow multiple users on a linux system use some common functions. The problem I am having is that for some users their default library location is .lib.loc = "/usr/lib/R/library" whereas for other users it is .lib.loc = "/usr/local/lib/R/library" It seems as though the packages (for example cluster) load fine if I just change .lib.loc to

Perhaps this is obvious...but is there anyway to create a matrix like object with has more than 2 dimensions. I want to estimate a bunch of var/cov matrices inside an index loop. It would be more computationally efficient to do this in C...but R makes many of the operations inside the loop really easy! Thanks. -- Tony Long Ecology and Evolutionary Biology Steinhaus Hall University of

Sorry: I should have reproduced the "problem" with a simple example. I do this below. I think there is likely a switch I can change using par, but don't know what it is. The problem is the tick marks for the Y- axis are only on plots in column #1 and for the X-axis in row # 2. Tony x <- 1:10 y <- 1:10*5 par(mfrow=c(2,2)) plot(x,y) plot(x,y) plot(x,y) plot(x,y)

I am trying to use dynamic loading of an outside C routine. I am attempting 6.12.1 of Phil Spector's book. When I try to load the object file I get an error I don't understand: > dyn.load("runa.o") Error in dyn.load(x) : unable to load shared library "/usr/home/tdlong/run_avg/runa.o": /usr/home/tdlong/run_avg/runa.o: ELF file's phentsize not the expected

All: I apologize as I think I had this problem before, and misplaced my notes on the solution. I just tried to upgrade my version of R on a Redhat Linux computer. I downloaded and ran the rpm for R-recommended-1.4.1-1.i386.rpm Problem is that when I type R from any directory the "old" version still seems to run. I can only guess this has to do with where the new and old

I am running R version ??? under Redhat 5.2. It seems as though the --nsize object has no effct on the size of the allocated Ncells as determined using gc(). Yes, I have that much data.... That is if I envoke R with R --vsize 100 --nsize 5000000 then type gc() I get free total Ncells 92202 200000 Vcells 12928414 13107200 Thanks Tony Long Ecology and Evolutionary Biology Steinhaus

Hello. The laboratory where I work has the possibility to get a Sun machine with 12 processors. My question is: can R be used to implememt parallel algorithms which take into account the several processors? Is there a way to run *threads* in R? If this is possible, would somebody share his/her experiences? Thanks. Isabel -- Isabel Cañette Iguá 4225 Centro de Matemática 11400

Hi, When using method L-BFGS-B along with a parscale argument, should the lower and upper bounds provided be on the scaled or unscaled values? Thanks. Cheers, -- Seb

Dear all I've got the dataset data:2743;4678;21427;6194;10286;1505;12811;2161;6853;2625;14542;694;11491; ?? ?? ?? ?? ?? 14924;28640;17097;2136;5308;3477;91301;11488;3860;64114;14334 I know from other testing that it should be possible to fit the data with the exponentialdistribution. I tried to get parameterestimates for the exponentialdistribution with R, but as the values of the parameter

Hi I am trying to recover the hessian of a problem optimised with box-constraints. The problem is that in some cases, my estimates are very close to the boundary, which will make optim(..., hessian=TRUE) or optimHessian() fail, as they do not follow the box-constraints, and hence estimate the function in the unfeasible parameter space. As a simple example (my problem is more complex though,

All: Any ideas on how to do variance component estimation, or at least get Expected Mean Sqaures out of the modeling commands. Thanks. Tony Tony Long Ecology and Evolutionary Biology Steinhaus Hall University of California at Irvine Irvine, CA 92697-2525 Tel: (949) 824-2562 (office) ****NOTE NEW AREA CODE**** Tel: (949) 824-5994 (lab) ****NOTE NEW AREA CODE****

I am generating an array of similar plots using the par(mfrow=c(3,3)) method. Everything works fine except the plot only puts y-axis tick marks on cells in column one and x-axis tick marks on cells in row three. I would like tick marks on both the x and y axix of all 9 plots in my array. I am generating plots using the following two functions three.by.three.plot <- function(ss) {

Dear all, I'd like tweaking the ... arguments that one user can pass in my function for fitting a model. More precisely, my objective function is (really) problematic to optimize using the "optim" function. Consequently, I'd like to add in the "control" argument of the latter function a "ndeps = rep(something, #par)" and/or "parscale =

Hi! This is a repost of an earlier message (with a clearer example demonstrating the problem I ran into). If you run the mle example in stats4 library(stats4) x <- 0:10 y <- c(26, 17, 13, 12, 20, 5, 9, 8, 5, 4, 8) ll <- function(ymax=15, xhalf=6) -sum(stats::dpois(y, lambda=ymax/(1+x/xhalf), log=TRUE)) (fit <- mle(ll)) plot(profile(fit),