similar to: question about glm vs. loglin()

This practical problem in maximum likelihood estimation must be encountered quite a bit. What do you do when a data point has a probability that comes out in numerical evaluation to zero? In calculating the log likelihood you then have a log(0) problem. Here is a simple example (probit) which illustrates the problem: x<-c(1,2,3,4,100) ntrials<-100 yes<-round(ntrials*pnorm((x-3)/1))

Hi everyone, I have a question regarding a C function of the "stats" package in R. I tried to understand the ?loglin? basic function of the ?stats? package implemented in R. The implemented function itself runs without any problem (perhaps see sample). When I ran it line by line it stopped at the lines 23-24 of the loglin-function; (the following line): z <- .Call(C_LogLin,

Hi All, I am trying to creat a simple example byusing ipf function in R, but i could not get it succefully...I am very new to R, does anyone could help, to instruct me about this ipf fucntion? Actually, this is what I mean 50 | 50 ---------------------- 33.4| 28.57 | 14.29 33.3| 23.81 | 4.762 33.3| 9.523 | 19.05

I am using the loglin function of the base package to fit log-linear models. I am interested in obtaining the parameter values and their standard errors. Parameters are easily obtained, but I haven't found the way of obtaining their standad errors. Is this possible with the loglin function? If not, is there any other function to get them? Many thanks, -- Vicente Piorno Departamento de Ecolox?a

I am fairly new to log-linear modelling, so as opposed to trying to fit modells, I am still trying to figure out how it actually works - hence I am looking at the interpretation of parameters. Now it seems most people skip this part and go directly to measuring model fit, so I am finding very few references to actual parameters, and am of course clear on the fact that their choice is irelevant for

Dear all, I have run a hierarchical log-linear analysis using loglin {stats} and came up with a specific model. loglin returns me the parameter estimates giving me an idea in which direction the observed frequencies deviate from the expected ones for my different factors. To assess the significance of any such effects I would need to calculate the ratio of the log-linear parameter

Hi, I'm analyzing experimental results where two different events ("T1" and "T2") can occur or not during an experiment. I made my experiments with one factor ("Substrate") with two levels ("Sand" and "Clay"). I would like to know wether or not "Substrate" affects the occurrence probability of the two events. Moreover, for each

Hello, I am almost new in R, so perhaps my question will be silly. I try to use R for analyzing capture-recapture data in epidemiology. A cancer registry has different sources of patients. We know in each list, patients already known in all other list. The aim is to use capture-recapture models for estimating the number of patients unknow of all the sources. Because no order in sources, one

Hi list! I'm computing multivar. distances from a set of centroids to a (large) set of individuals. I'm now just using rbind to create a matrix (x) with the centroid and the individuals, then run as.matrix(dist(x)) and finally select the appropriate columns, as I'm not interested on the distances among individuals. Therefore, this procedure implies a waste of computing time. Is there

Hi, We have some sample data from the US census, and we know the marginal totals for the population. We need to make the population estimates add up to the correct sums. I have two questions: Is there some package in R which does this adjustment, by any means? Is there some more modern reference for this problem than Deming's 1943 monograph, ``Statistical Adjustment of Data''?

Hi, It appears that there is no package for estimating log linear models (L. Goodman's family) for data in the form of frequency tables. Am I wrong? Thanks Marwan Khawaja Research Coordinator Fafo, Institute for Applied Social Science N-0608 Oslo, Norway Tel +47 22 08 86 00 +47 22 08 86 94 (Direct) +47 22 67 33 05 (Private) Fax +47 22 08 87 00

Hello, I'm planning to start using R. Before getting into it, I'd like to ask a couple of questions. Does R carry out loglinear model analysis? That is, will it provide the chi-squared goodness of fit test statistic for a given hierarchical loglinear model? Maybe even do a model selection procedure (like Brown's two-step procedure, or forward/backward selection)? Thanks

Hi, we try to do a logistic regression with the function glm. But we notice that this function don't give the same results as the SAS proc catmod (differents estimate given). We try to change the contrast on R system with: > options(contrasts=c(unordered="contr.SAS",ordered="contr.poly")) We also try with brlr and logistf functions. Unfortunately, the estimate

Hello to all, I recently downloaded R to my PC and am enjoying getting acquainted with it. Thank you to everyone involved in the R-project! I am interested in doing a log-linear analysis with R on a data set with dichotomous variables. There are 11 variables (columns) and around 1000 subjects (rows). How do I aggregate my data, i.e. how do I make a new dataset that includes the variable giving

Hello, at the moment I am doing quite a lot of regression, especially logistic regression, on 20000 or more records with 30 or more factors, using the "step" function to search for the model with the smallest AIC. This takes a lot of time on this 1.8 GHZ Pentium box. Memory does not seem to be such a big problem; not much swapping is going on and CPU usage is at or close to

Dear useRs I am looking for a way to randomise the values within a matrix: the conditions are that the sums of the rows and the sums of the columns should remain the same as in the original matrix. Any help would be appreciated Cheers Yann

Hello All: I know the function loglin() and loglm() from librarary(MASS) performs analysis on nominal categorical data. Are there any libraries, functions or examples available for analysis of ordinal categorical data? I have in mind procedures that can replicate results in Alan Agresti (1984) "Analysis of Ordinal Categorical Data." Thanks, ANDREW

Dear R-helpers, Im trying to fit a Log-linear model on a dataset with bird counts from 60 sites over 14 years for 12 months each (factors for the models). One of the aims is to predict the missing values in this dataset with model predictions. Ive first tried to work with GLM's, that worked fine except for models with one or more interaction-terms. The GLMs run, run .. for hours. So I

Dear Sirs, I am trying to compile R v1.2.1 under Digital Unix 4.0D. The configure-script runs without any problems but during 'make' I receive the following error-message: [......] g77 -mieee -g -O2 -c dtrco.f -o dtrco.o g77 -mieee -g -O2 -c dtrsl.f -o dtrsl.o g77 -mieee -g -O2 -c eigen.f -o eigen.o g77 -mieee -g -O2 -c lminfl.f -o lminfl.o ar cr libappl.a Rsock.o approx.o bakslv.o

On 2015-10-15 15:02, Prof Brian Ripley wrote: > On 15/10/2015 13:32, Michael Felt wrote: >> Hi. >> >> Just wanted to let you know I am getting close to packaging R for AIX in rephrase - would like to be active in keeping R binaries current for AIX. My interest in not in R per se (rather a colleague who has a project that uses R, so I hope to assist him, and others like him).