similar to: Positive log-likelihood in lme

Hi All, Does someone have an idea of how to cleverly convert a categorical timeseries into a transition matrix? Ie, I have something like: x<- c(1,1,2,1,1,2,2,2,1,2), And I want a matrix with counts and/or probabilities: > tr <- matrix(c(2,3,2,2),2,2) > tr [,1] [,2] [1,] 2 2 [2,] 3 2 Meaning that there are two transitions from 1 to 1, two from 1 to 2, three from 2 to 1

Kia ora list members: I'm having a little difficulty getting the correct standard errors from a glm.object (R 1.9.0 under Windows XP 5.1). predict() will gives standard errors of the predicted values, but I am wanting the standard errors of the mean. To clarify: Assume I have a 4x3x2 factorial with 2 complete replications (i.e. 48 observations, I've appended a dummy set of data at the

Dear All, Apologies for this simple question and thanks in advance for any help given. I want to make from my .R script an .exe file. Is there any way to transfort my script to an autolaunch file? It means it runs the script by double clicking on it. p.s.: I'm using windows -- View this message in context: http://www.nabble.com/executable-script-tf4806651.html#a13751752 Sent from the R

Dear R community, I am looking for an R package or other software to study hidden Markov models. I need to be able to incorporate multivariate emissions and covariates for the transition probabilities. The msm package seems almost perfect for my purpose, but I do not think it allows multivariate emissions. I will be grateful for your suggestions. All the best, -- Emilio A. Laca One

-- R Help List -- I am looking for a bivariate normal cdf routine in R. I have some fortran routines for this, which appear to be based on 15-point quadrature. Any guidance/suggestions on making these in loadable R-functions would be appreciated. Thanks, Dan =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-= Daniel A. Powers, Ph.D. Department of Sociology University of Texas at Austin

Dear useRs, I'm trying to create a barplot like so: x=matrix(1:10,2,5) barplot(x,leg=c("left","right"),besid=T) The legend is placed in default position topright, however the data are plotted there too. I tried controlling the legend position by adding x="topleft" but this results in an error that x matches multiple formal arguments. Leaving out the legend

Dear R-people: François Michonneau's method to obtain the special character plus/minus works on Windows 2000 professional. Many Thanks to François for his work! Phil Smith Centers for Disease Control and Prevention Atlanta, GA _____ From: François MICHONNEAU [mailto:francois.michonneau@gmail.com] Sent: Monday, March 20, 2006 1:58 PM To: r-help@stat.math.ethz.ch; Smith, Phil

Hi I have a data.frame with dim = 18638 (rows) 6 (cols) names(dat) [1] "id" "long" "lat" "species" "type" "size" Variable "species" and "type" are factors. Species has 5 levels "BOV" "CAP" "CER" "OVI" "POR" Variable "type" has 11 levels

Dear all, does anyone have r code to perform model-averaging of regression parameters by Akaike weights, and/or to do all-possible-subsets lm modelling that reports parameter estimates, AICc and number of parameters for each model? I have been looking for these in the archive but found none. (I am aware that many of you would warn me against these methods advocated by Burnham and Anderson

Hello, I tried to fit a poisson distribution but looking at the function fitdistr() it does not optimize lambda but simply estimates the mean of the data and returns it as lambda. I'm a bit confused because I was expecting an optimization of this parameter to gain a good fit... If I would use mle() of stats4 package or mle2() of bbmle package, I would have to write the function by myself

Hello All, Does anyone know of a package that performs constraint-based clusters? Ideally the package could perform "Time-Ordered Clustering", a technique applied in a recent journal article by Runger, Nelson, Harnish (using MS Excel). Quote, "in our specific implementation of constrained clustering, the clustering algorithm remains agglomerative and hierarchical, but observations

Dear R users, I'm trying to fit a simple random intercept model with a fixed intercept. Suppose I want to assign a weight w_i to the i-th contribute to the log-likelihood, i.e. w_i * logLik_i where logLik_i is the log-likelihood for the i-th subject. I want to maximize the likelihood for N subjects Sum_i {w_i * logLik_i} Here is a simple example to reproduce

I have two matrixes, red: a 123 c 200 d 400 e 650 g 127 f 100 and blue: a 10 b 20 c 30 d 40 e 50 f 60 g 70 is there any easy way to get the next matrix: a 10 123 b 20 0 c 30 200 d 40 400 e 50 650 f 60 100 g 70 127 i.e. to add in the third column of blue the [,2] values of red corresponding to the file with same [x,1] value of blue, adding a cero in the case that there is no [x,1]

Hi All, I have a 1000x1000000 matrix. The calculation I would like to do is actually very simple: for each row, calculate the frequency of a given pattern. For example, a toy dataset is as follows. Col1 Col2 Col3 Col4 01 02 02 00 => Freq of ?02? is 0.5 02 02 02 01 => Freq of ?02? is 0.75 00 02 01 01 ? My code is quite simple as the following to find the pattern ?02?.

Hello everyone, I have a dataset in the following format: col1 col2 # # # # # # # # # # # # What I want to do is: loop a random sample 10 times, and for each time it is sampled I want to run a correlation between both columns. What I have so far is this: >feb <- read.csv("corr.csv") # where the dataset is for February >attach(feb) >for(i in

Hi. How do I plot the straight line and r? in a scatter plot using a simple file x~y? Sueli Rodrigues Eng. Agr?noma - UNESP Mestranda - USP/ESALQ PPG-Solos e Nutri??o de Plantas Fones (19)93442981 (19)33719762

Dear All, When installing the Ruuid package (from Bioconductor) from sources on my MAC (OS X 10.3.5, R version 2.0.0) I get the following errors: m00245:~ ivisser$ R CMD INSTALL -l /Users/ivisser/Library/R/library/ /Users/ivisser/Desktop/Ruuid * Installing *source* package 'Ruuid' ... loading cache ./config.cache checking for glib-config... no checking how to run the C preprocessor...

To all, Apologies if this question has already been asked but I can't find anything. I can't seem to think of more specific search terms. I want to display/create a file of a pure plot with a specific height and width. I want to utilise every single pixel inside the axes. I do not want to display any margins, legends, axes, titles or spaces around the edges. Is this possible?

Dear R-helpers, I'm trying to transfer a loop from R code to C to improve performance using the .Call interface. However, I ran into problems before even getting started, and I hope (fear) I'm missing something completely obvious here. I use the following C function (passing an integer to the C function and printing it): #include <R.h> #include <Rinternals.h> SEXP

Hello list, I am dealing with a noisy function (gradient,hessian not available) with simple boundary constraints (x_i>0). I've tried constrOptim() using nelder mead to minimize it but it is way too slow and the returned results are not satisfying. simulated annealing is so hard to tune and it always crashes R program in my case. I wonder if there are any packages or functions can do