Displaying 3 results from an estimated 3 matches for "dpmolmm".
2009 Aug 10
0
ordinal response model with spatial autocorrelation
...s to make a mixed effects model with random factors capturing the
different sampling regions as ideal. I failed however to find a function
in nlme/lme4 or other packages capable of fitting ordinal data, and
package 'DPpackage' uses an approach I am not really familiar with; the
function DPMolmm also triggers errors, even for the provided examples.
There is no sound a-priori reason to believe that the proportional odds
assumptions apply - they may, or may not. Anyways I don't have any
preference to that specific kind of model, so any type of ordinal
response model would be much app...
2007 May 29
0
DPpackage - New version
...r mixed effects model.
2.2) DPglmm and DPMglmm, using a DP/MDP and DPM of normals prior,
respectively, for generalized linear mixed effects models,
respectively. The sampling(link) considered by these functions are
binomial(logit,probit), poisson(log) and gamma(log).
2.3) DPolmm and DPMolmm, using a DP/MDP and DPM of normals prior,
respectively, for the probit-ordinal mixed effects models.
2.4) DPrasch and FPTrasch, using a DP/MDP and finite PT/MPT
(mixture of Polya Trees) prior for the Rasch model with binary
sampling distribution, respectively.
2.5) DPraschpoisson an...
2007 May 29
0
DPpackage - New version
...r mixed effects model.
2.2) DPglmm and DPMglmm, using a DP/MDP and DPM of normals prior,
respectively, for generalized linear mixed effects models,
respectively. The sampling(link) considered by these functions are
binomial(logit,probit), poisson(log) and gamma(log).
2.3) DPolmm and DPMolmm, using a DP/MDP and DPM of normals prior,
respectively, for the probit-ordinal mixed effects models.
2.4) DPrasch and FPTrasch, using a DP/MDP and finite PT/MPT
(mixture of Polya Trees) prior for the Rasch model with binary
sampling distribution, respectively.
2.5) DPraschpoisson an...