similar to: Fw: likelihood ratio test

Dear R-help, Can anybody tell me which R package has Lo-Mendell Rubin LR test and Bootstrap LR test to compare the model fit between k class and k+1 class model for Latent class analysis? Thanks in advance,  warn regards,Ms.Karunambigai M PhD Scholar Dept. of Biostatistics NIMHANS Bangalore India [[alternative HTML version deleted]]

I am doing hierarchical clustering with cluster package.  I couldnot find similarity measures like matching coefficient, Jaccard coefficient and sokal and sneath. Could anyone please tell package with similarity measures for binary data? kind regards, Ms.Karunambigai M PhD Scholar Dept. of Biostatistics NIMHANS Bangalore India From cricket scores to your friends. Try the Yahoo! India

Dear R-help, I am doing clustering via finite mixture model. Please suggest some packages in R to find clusters via finite mixture model with continuous variables. And also I wish to verify the distributional properties of the mixture distributions by fitting the model with lognormal, gamma, exponentials etc,. Thanks in advance,  warm regards,Ms.Karunambigai M PhD Scholar Dept. of Biostatistics

hi all, I am doing hierarchical clustering using similarity measures for binary data using package ade4 and hclust function. For method=8 and method = 9 of dist.binary, I am getting Na values. Hence, hclust function is giving error as Error in hclust(d8, method = "ward") :   NA/NaN/Inf in foreign function call (arg 11). I think the fact that due to zero in the denominator of the

hi, I want to do hierarchical clustering with Jaccord index. I tried to do with vegan package for finding index and hierarchical clustering with hclust function. While doing clustering it is showing an error message as "invalid distance method". I would be grateful if anyone tells how to rectify the error. Thanks in advance,   kind regards, Ms.Karunambigai M PhD Scholar Dept. of

hi, I am trying to calculate distance matrices for binary data frame. I am using dist.binary in 'ade4' package. This is the code i run and get error message as 'missing value where True/False needed: clss <- as.data.frame(cls) dist.binary(clss, method = 1, diag = FALSE, upper = FALSE) Also, if i convert the factors into numeric(i.e,1&2 in the place of 0&1 for present/absent

hi r-help, i am doing kmeans clustering in stats. i tried for five clusters clustering using: kcl1 <- kmeans(as1[,c("contlife","somlife","agglife","sexlife",                         "rellife","hordlife","doutlife","symtlife","washlife",                       

Not only do FPGAs not support recursion, we don’t even support calls! All user code must be inlined into one kernel/component, which is then used to create HDL for the FPGA. Mark From: Bruce Hoult <brucehoult at sifive.com> Sent: December 17, 2018 9:28 AM To: Mendell, Mark P <mark.p.mendell at intel.com> Cc: jjones at prc-hsv.com; LLVM Developers Mailing List <llvm-dev at

-- Thanks & Regards, Kamal Kishore Research Scholar Department of Biostatistics National Institute of Mental Health and Neuro Sciences (NIMHANS) Banglore-560029 Mob-+91-9591349768 Email:kamalkishorestats@gmail.com [[alternative HTML version deleted]]

It seems to me that R returns the unpenalized log-likelihood for the ratio likelihood test when ridge regression Cox proportional model is implemented. Is this as expected? In the example below, if I am not mistaken, fit$loglik[2] is unpenalized log-likelihood for the final estimates of coefficients. I would expect to get the penalized log-likelihood. I would like to check if this is as expected.

I'm applying logistic regression to a moderate sized data set for which I believe Wald based confidence intervals on B coefficients are too conservative. Some of the literature recommends using confidence intervals based on the likelihood ratio in such cases, but I'm having difficulty locating a package that can do these. Any help would be immensely appreciated. Best, Jeff Hanna --

Hello, I would like to get the likelihood ratio and score tests for specific variables in a multivariate coxph model. The default is Wald, so the tests for each separate variable is based on Wald's test. I have the other tests for the full model but I don't know how to get them for each variable. Any idea? David Biau. [[alternative HTML version deleted]]

Dear All, I fitted two non-nested proportional hazards models using the coxph() function from package survival. Now, I would like to apply a model selection test like, e.g., the likelihood ratio test proposed by Vuong. I found an implementation of Vuong's test in the package 'pscl', but that does not work for cox models. Is there any package available that provides an

Dear R helpers, >From the lrm( ) model used for binary logistic regression, we used the L.R. model value (or the G2 value, likelihood-ratio chi-squared statistic) to evaluate the goodness-of-fit of the models. The model with the lowest G2 value consequently, has the best performance and the highest accuracy. However our model includes rsc() functions to account for non-linearity. We

Hopefully a quick question: is there a package/routine to perform Box's M (like proc discrim in SAS) or some other test for whether two multivariate samples (presumed multivariate normal) have the same v-c matrix? I've looked, but can't find it. If not, I can certainly code it up myself (and perhaps submit it for inclusion in the mvtnormtest package), but I wanted to check if it

I am analysing some binary data with a mixed effects model using glmmPQL. I am aware that I cannot use the AIC values to help me find the minimum adequate model so how do I perform likelihood ratio tests? I need to fix on the minimum adequate model but I'm not sure of the proper way to do this. Thank you very much, Elizabeth Boakes Elizabeth Boakes PhD Student Institute of Zoology

Is there any package available in R to do the following hypothesis tests? Testing the means of two Poissons (equivalent to the difference of two proportions) Testing the equality of two proportions from binomials Testing the equality of proprtions of two negative binomials (both conditional and unconditional tests). No large sample approximation tests...I need exact tests Thanks, Jim

Dear Peter, I am running your g.test() with the william's correction but I have a question about the input numbers. These are my data: "Our data are consistent with those obtained using microarray comparative genome hybridization in that we found significantly fewer variants per Mb on the X compared to the autosomal chromosomes (152 versus 336 respectively, G = 93.4, P < 2e-16, df =

Hi All I have to run multiple stimations and to compute Likelihhod ratio. If I compute ls function with coef and summary I can extract "outputs" that I need. I am not able to find something similar to log liklihood.... Can you pease tell me running a ls function x on y how to extract if posible LR statitic or Likelihood or Log likelihood. Many thanks in advance. If you send me

Dear R list, From the lrm() binary logistic model we derived the G2 value or the likelihood-ratio chi-squared statistic given as L.R. model, in the output of the lrm(). How can this value be penalized for non-linearity (we used splines in the lrm function)? lrm.iRVI <- lrm(arson ~ rcs(iRVI,5), penalty=list(simple=10,nonlinear=100,nonlinear.interaction=4)) This didn’t work