similar to: help on voung test

Dear All, I am using the function vuong of the package pscl to compare 2 non nested glm models with a numeric response. I did the following m1<-glm(y ~x ,data=xxx) m2<-glm(y ~z , data=xxx) When calling the vuong function I get the following message: > vuong(m1,m2) Error in predprob.glm(m1) : your object of class glm is unsupported by predprob.glmyour object of class lm is unsupported

Dear All, I am using the function vuong from pscl package to compare 2 non nested models NB1 (negative binomial I ) and Zero-inflated model. NB1 <-  glm(, , family = quasipoisson), it is an object of class: "glm" "lm" zinb <- zeroinfl( dist = "negbin") is an object of class: "zeroinfl"   when applying vuong function I get the following: vuong(NB1,

Dear All, I would like to know if the Voung test (Voung; Econometrica, 1989) to compare two non-nested regression models has been implemented in R. Thanks in advance for your assistance, mirko [[alternative HTML version deleted]]

I want to compare the poisson and the zero-inflated poisson distribution on describing the data. So, after using the GLM and the ZEROINFL function, I used the Voung function to compare them. Here is my code: library(pscl) glm1 <- glm(nmer9_1[, 1] ~ 1, family = poisson) zip <- zeroinfl(nmer9_1[, 1] ~ 1) vuong(glm1, zip) However, R returns the following error message: "Error: cannot

I would like to test in R what regression fits my data best. My dependent variable is a count, and has a lot of zeros. And I would need some help to determine what model and family to use (poisson or quasipoisson, or zero-inflated poisson regression), and how to test the assumptions. 1) Poisson Regression: as far as I understand, the strong assumption is that dependent variable mean = variance.

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 all, I want to build a model in R based on animal collection data, that look like the following Nr Village District Site Survey Species Count 1 AX A F Dry B 0 2 AY A V Wet A 5 3 BX B F Wet B 1 4 BY B V Dry B 0 Each data point shows one collection unit in a certain Village, District, Site, and Survey for a certain Species. 'Count' is the number of animals collected in that

Hi, I have two questions. First, I'd like to compare a ZINB model to a negativ binomial model with the Vuong test, but I can't find how to performe it from the zicount package. Does a programm exist to do it ? Second, I'd like to know in which cases we have to use a double hurdle model instead of a zero inflated model. Many thanks, St??phanie Payet REES France R??seau

Dear UseRs, I have a very simple question. I have a big matrix (say x) including probabilities (values in (0,1)). I have to store in a list the names of the row and the column where max(x) is located. How can I proceed? Thanks in advance for your assistance! mirko

Hello. I am running 9 poisson regressions with 5 predictors each, using glm with family=gaussian. Gaussian distribution fits better than linear regression on fit indices, and also for theoretical reasons (e.g. the dependent variables are counts, and the distribution is highly positively skewed). I want to determine pseudo R^2 now. However, using the pR2() of the pscl package offers drastically

Dear R-users, I am new to the list and I would like to submit (probably!!!!) a stupid question: I found in a paper a reference to a t-test for the evaluationg the difference between the standard deviations of 2 samples. This test is performed in the paper but the methodology is not explained and any reference is reported. Does anyone know where I can find references to this test and if it is

Dear R users, I'm trying to fit a gamma-frailty model on a simulated dataset, with 6 covariates, and I'm running into some results I do not understand. I constructed an example from my simulation code, where I fit a coxph model without frailty (M1) and with frailty (M2) on a number of data samples with a varying degree of heterogeneity (I'm running R 2.3.1, running takes ~1 min).

Hi, I''m trying to get a handle on hfsc. Here is my configuration: root@jmnrouter:/jmn# tc class show dev vlan1 class hfsc 1: root class hfsc 1:1 parent 1: ls m1 0bit d 0us m2 225000bit ul m1 0bit d 0us m2 225000bit class hfsc 1:10 parent 1:1 rt m1 191000bit d 25.0ms m2 135000bit ls m1 0bit d 0us m2 135000bit ul m1 0bit d 0us m2 225000bit class hfsc 1:20 parent 1:1 rt m1 22008bit d

Hello NG, I'm new in this group and I have a problem. the game commandos from pyro studios are not running. I post the error message at the end ... Any hints for me? *********************************** mirko@mirko:~$ wine --debugmsg warn+all /cdrom/Setup.exe warn:dosfs:DRIVE_Init Drive B: not defined warn:dosfs:DRIVE_Init Drive E: not defined warn:dosfs:DRIVE_Init Drive F: not defined

Dear list, I have the following problem. I have a data frame like this CLUSTER YEAR variable Delta R_pivot M1 2005 EC01 NA NA M1 2006 EC01 2 NA M1 2007 EC01 4 5 M2 2005

Dear Friends, My problem is related to how to measure probabilities from a probit model by changing one independent variable keeping the others constant. A simple toy example is like this Range for my variables is defined as follows y=0 or 1, x1 = -10 to 10, x2=-40 to 100, x3 = -5 to 5 Model output <- glim(y ~ x1+x2+x3 -1, family=binomial(link="probit")) outcoef <-

Hello list, I am now using hfsc for QOS. I have something like this: tc qdisc add dev ethx root handle 1: hfsc default 9 tc class add dev ethx parent 1: classid 1:1 hfsc ls m2 70mbit ul m2 70mbit tc class add dev ethx parent 1:1 classid 1:9 hfsc ls m2 7mbit #DNS stuff follows tc class add dev ethx parent 1:1 classid 1:2 hfsc rt m1 12mbit d 1ms m2 1mbit #Half-life tc class add dev ethx parent

Hi all, I have been trying to use zeroinfl() with the pscl package with R version 2.1.1. and with the newest versions of the contrib packages compatible with R 2.1.1. I have read the examples, the vignette and all the posts relating to zeroinfl() but I am still confused as to how to structure the model. Here is a small example; the error message is the same for big data sets

Dear list, I'll try to be more clear in explaining my problem. I have a data frame like this called X: CLUSTER YEAR variable value1 value2 M1 2005 EC01 NA NA M1 2006 EC01 2 5 M1 2007

Hi all, I have an experiment that this: Moths's behavior, where 0 is not behavior and 1 is behavior I look the moths every 10 minutes for 960 minutes/day for 7 days. Exist an interval of the 480 minutes between the days with no observations My dataset is something like this: ------------------------------------ | day | minutes | moth | behavior | ------------------------------------ | 1 |