similar to: models for polytomous data

Hello I have several replicates (30) of a -- short -- time series (19 obs) and I'd like to estimate the first few lags autocorrelation function. Is there an immediate way of handling multiple realizations when computing the ACF in R? I'm using R-1.4.1 on a Linux Debian box. Thanks in advance claudia ------------------------------------------------------------------------- claudia

I'm running R-1.4.1 on a linux debian (version 2.2) box. I've tried to upgrade to R-1.6.0, and the execution of make halts with the following error messages: make[4]: Entering directory `/home/tebaldi/R/R-1.6.0/src/library/methods' dumping R code in package 'methods' Error in testRversion(descfile) : This package has not been installed properly See the Note in ?library

There is probably an elegant and efficient way to do this -- perhaps already implemented, and some of you knows it. Myself, I'm getting stuck in long loops ... Here is the question: I have a long (80,000 + obs) binary time series. For each of its elements I'd like to compute and save in a vector "the number of steps 'til the first switch of state happens". For example,

Hi all I'm running lm()/leaps() kind of computations within a loop, and I submitted the entire thing by sourcing a file of R code in interactive mode. I'd like to interrupt the evaluation of this (it's taking way too long) but I am not able to. I'm running R-1.3.0 from an emacs window (ESS-5.0) and I'm on a linux box, (Debian). I tried Control-c Control-c (nothing happens),

Hi I'm trying to print several plots to a multi-page postscript file. Some plots are output of basic commands, some are produced by "trellis" commands (from the package lattice). Right now I'm not able to get a straightforward black and white color scheme for the latter kind: when I open the postscript file the "trellis" plots are invisible, or parts of them are

Hello I'm upgrading from R-1.4.1 to R-1.5.1, locally on my Linux PC running Debian. after running 'configure' this is what I get (just in case it helps figuring out what follows later...) R is now configured for i686-pc-linux-gnu Source directory: . Installation directory: /usr/local C compiler: gcc -D__NO_MATH_INLINES -mieee-fp -g -O2 C++

Dear R-helpers, I'm plotting geophysical data in the form of contours using "filled.contour". The display would be much more effective if the areas with negative values could be color coded by -- say -- "cold colors" in the range of blue to green, and conversely the areas with positive values got plotted with "warm colors", from yellow to red. Right now if I use

I'd like to apply the ideas of Pinheiro et al. (1997): "Robust Estimation in LInear Mixed Effects Models using the Multivariate t-Distribution" and I'm wondering if the EM-based estimation described in that paper has been implemented by somebody in R already (I'm assuming it's not yet available within the package nlme -- whose subtitle is "Fit and compare

Here is the answer to an old question of mine, regarding maps in R Hope this help. claudia ---------- Forwarded message ---------- Date: Mon, 25 Jun 2001 13:48:05 -0400 From: Kieran Healy <kjhealy at Princeton.EDU> To: Claudia Tebaldi <tebaldi at ucar.edu> Subject: Re: [R] maps in R Hi Claudia -- you can get the maps() library from here:

Hello Is there a simple way of fitting a 'smooth curve' to a time series with the additional constraint that the first derivative be not negative? I know that if I choose a "large enough" window for a moving average sort of filter on my data I end up with a non-decreasing curve anyway, but I'm wondering if there is a pre-built method that can include the constraint from

Hi all Just this morning I upgraded to R 2.12.0 (for Mac OS X 10.6.4). All went well until I needed to run a help() or help.search() in my session, which I'm running within Emacs (ESS 5.3.7). Say I need help with the command 'density'. When I type help(density) or ?density the ESS help buffer opens, it is titled *help[R](density)* but it contains only a couple of lines saying,

Dear R-helpers, I have lat/lon coordinates of regularly spaced grid points, about 4Km apart, covering the entire US continental region. I would like to mask this rectangular grid in order to extract all and only the grid points within a specific region. Today I want to extract Montana, say, from this grid, and I am hoping to somehow use the returned value of the function

Hello I'm trying to render in 3D what I usually plot by image(), or image.plot() from the library fields, followed by a map("world",add=TRUE) type of command. More concretely, I have a field of temperature values, for a given geographic area, and I would like to plot a 3D surface whose x and y axes consist of longitude and latitude values and whose height and color-coding correspond

I am new to generalized linear models and studying McCullagh & Nelder (1989). Especially, I have a problem resembling the \"cheese taste\" example (5.3.1. p. 109) of the book. I tried to analyse the cheese example with R but failed to do so because R allowed me to use logit link function only with binary family that supposes 0 <= y <= 1. Do I need to scale the y\'s or

I thought I had plotted a map of oregon and washington and overlayed some points using R. Is that possibe since I can't seem to find the source file I used or commands for plotting maps and points? If not, sorry for the bother... Thanks, Jeff. Jeff D. Hamann Hamann, Donald & Associates, Inc. PO Box 1421 Corvallis, Oregon USA 97339-1421 Bus. 541-753-7333 Cell. 541-740-5988 jeff_hamann

Dear community, I'm currently attempting to predict the occurence of an event (factor) having more than 2 levels with several continuous predictors. The model being ordinal, I was waiting the glm function to return several intercepts, which is not the case when looking to my results (I only have one intercept). I finally managed to perform an ordinal polytomous logisitc regression with the

Greetings, I hope this isn't obvious but I've read through the FAQ and the various other R/S books I have and I cannot, for the life of me, figure out how to sort a data frame by a specific variable. Suppose I have a four variable data.frame x and the variables are var1, var2, var3, var4. I want to sort on say var3 simply for display purposes. How can this be accomplished? Thanks

Hi all I'm plotting colored contour maps using filled.contour. My levels are very unevenly spaced, with, say, high resolution in the small numbers but ranges that can be an order of magnitude or two larger in absolute value compared to where the action takes place. Aside from transforming the data, is there a way to control the color spacing in the key to the right of the map? Right now I

Hello I'm having trouble figuring out how to use the output of "segmented()" with a new set of predictor values. Using the example of the help file: ??set.seed(12) xx<-1:100 zz<-runif(100) yy<-2+1.5*pmax(xx-35,0)-1.5*pmax(xx-70,0)+15*pmax(zz-.5,0)+rnorm(100,0,2) dati<-data.frame(x=xx,y=yy,z=zz) out.lm<-lm(y~x,data=dati) o<-## S3

Hello list, Is there any mean to fit models for ordinal response other than multinomial polytomous ("multinom" from nnet ) and cumulative logit ("polr" from MASS)? I am particularly interested in continuation-ratio model and adjacent-category logit model. It is for the sake of epidemiology in wild-living populations! Many thanks, Emmanuelle Fromont