similar to: Syntax for getting covariance matrix

Hello, Is there a way to obtain the variance-covariance matrix of the estimated parameters from GLM? my.glm<-glm(mat ~X,family = binomial, data =myDATA) out1<-predict(my.glm,se.fit = TRUE) std<-out1$se.fit se.fit is for getting the standard errors of the estimated parameters (\betas). Is there a way to get the variance-covariance matrix of the estimated parameters? Many thanks,

Hello I am running a project but I encounter a problem . I would be happy to receive help : problem: I have a binary dependent variable and some covariates logit(y)=a+bx+cz . I want to estimate the score vectors and their covariance by the usage of logit function and so glm in R .The vlaue of one of the coefficient ( like b) is known previously and I want to extract a and c and covariance

Hi, I am running a simple linear model with (say) 5 independent variables. Is there a simple way of getting the variance-covariance matrix of the coeffcient estimates? None of the values of the lm() seem to provide this. Thanks in advance, Ritwik Sinha rsinha@darwin.cwru.edu Grad Student Case Western Reserve University [[alternative HTML version deleted]]

Dear All,   is there a function in R that would help me convert a covariance matrix built based on arithmetic returns to a covariance matrix from log-returns?   As an example of the means and covariance from arithmetic:   mu <-c(0.094,0.006,1.337,1.046,0.263) sigma

Greetings, Cohen, Cohen, West, and Aiken 2003 (Applied Multiple Regression-Correlation Analysis for the Behavioral Sciences, Third Edition) on page 273 state the covariance matrix of the regression coefficients is provided by standard programs for multiple regression, including SAS, SPSS, and SYSTAT. How can it be calculated with R. Thank you very much. pbm Peter B. Mandeville cel:

Dear friends, After fitting a generalized linear models ,i hope to get the variance of alpha,variance of beta and their covariance, that is , the variance-covariance matrix/information of alpha and beta , suppose *B* is the object of GLMs, i use attributes(B) to look for the options ,but can't find it, anybody knows how to get it? > attributes(B) $names [1] "coefficients"

Hi, R developers. when running mle inside a loop I found a nasty behavior. From time to time, my model had a degenerate minimum and the loop just crashed. I tracked it down to "vcov <- if (length(coef)) solve(oout$hessian)" line, being the hessian singular. Note that the minimum reached was good, it just did not make sense to calculate the covariance matrix as the inverse of a

Hallo! I want to understand / recalculate what is done to get the CI of the logistic regression evaluated with lrm. As far as I came back, my problem is the variance-covariance matrix fit$var of the fit (fit<-lrm(...), fit$var). Here what I found and where I stucked: ----------------- library(Design) # data D<-c(rep("a", 20), rep("b", 20)) V<-0.25*(1:40) V[1]<-25

I have a question, I generated some data and tried survreg to analyze them, but here, I want to get the covariance matrix of the coefficients. I know how to get corr from survreg, say, summary(f,corr=T), but how to get covariance matrix of the coefficient ? can I put them in a matrix and output ? thanks below is what I did <mailto:r-help@stat.math.ethz.ch> n=100; beta=1.0

In "lm" command, we can use "vcov" option to get variance-covariance matrix. Does anyone know how to get variance-covariance matrix in nlrq? Thanks, Kate [[alternative HTML version deleted]]

Dear R-users, I would like to compute a robust covariance matrix of two series of realizations of random variables: ###Begin Example### data <- cbind(rnorm(100), rnorm(100)) model <- lm(data ~ 1) vcov(model) library(sandwich) NeweyWest(model) #produces an error ###End Example### NeweyWest() produces an error but sandwich(), vcovHAC(), kernHAC, weave(),... do not produce any errors. It

I want to predict a set of proportions from a linear regression using glm. The model includes a logit link. However I want to extract the variance:covariance matrix among the predicted proportions rather than on the logit scale. Is there a way to do this using Vcov or a similar package in R? Thanks Chris

Hello I am fitting a Cox PH model using the function coxph(). Does anyone know how to obtain the estimate of the covariance matrix under the null hypothesis. The function coxph.detail() does not seem to be useful for this purpose. Thanks, KD. [[alternative HTML version deleted]]

R 2.2.0 windows XP How can I perform a regression analyses using a vector of means, a variance-covariance matrix? I looked at the help screen for lm and did not see any option for using the afore mentioned structures as input to lm. Thanks, John John Sorkin M.D., Ph.D. Chief, Biostatistics and Informatics Baltimore VA Medical Center GRECC, University of Maryland School of Medicine Claude D.

Win2k, R1.6.2. I've been using Splus 6.1 and wanted to try the same regression analysis in R. Using "names( blah.lm )" in R yields [1] "coefficients" "residuals" "effects" "rank" [5] "fitted.values" "assign" "qr" "df.residual" [9] "xlevels"

Does anyone know how to do an Hausman test? I?ve estimate a modell (some alternatives) with clogit an wanted to test the IIA test (Independence of Irrelevant Alternatives) after estimating a multinomial logit model? Thank you

Say I fit a logistic model and want to calculate an odds ratio between 2 sets of predictors. It is easy to obtain the difference in the predicted logodds using the predict() function, and thus get a point-estimate OR. But I can't see how to obtain the confidence interval for such an OR. For example: model <- glm(chd ~age.cat + male + lowed, family=binomial(logit)) pred1 <-

Hi, I would like to use the sem package to perform a path analysis (no latent variables) with a mixture of 2 nominal exogenous, 1 continuous exogenous, and 4 continuous endogenous variables. I seek advice as to how to calculate the appropriate covariance matrix for use with the sem package. I have read through the polycor package, and am confused as to the use of "numeric" for

Hello everyone., I am looking for a covariance function this not the first time I have this type of problem (to find which function does something). I try in google with "R cran covariance function" but usually this ends with different results that do not help me that much. Could you please try to advice me how to search for what function implements the functionality you want.

I would appreciate confirmation that the function vcov(model.nlme) gives the var-cov matrix of the fixed effects in an nlme model. Presumably the random-effects var-cov matrix is given by cov(ranef (model.nlme)? Rob Forsyth