search for: mermcmc

The following I do not understand, but then I did'nt really use S4 methods ... > showMethods(plot) Function: plot (package graphics) x="ANY" x="lmList.confint" x="merMCMC" (inherited from: x="ANY") > plot(x=moda0MCMC) Error in as.double(y) : cannot coerce type 'S4' to vector of type 'double' > class(moda0MCMC) [1] "merMCMC" attr(,"package") [1] "lme4" Kjetil

...le mistake. Thanks in advance! > data(ratdrink, package = 'faraway') > rd.er <- lmer(wt ~ weeks*treat + (1 | subject), data = ratdrink) > rd.mc <- mcmcsamp(rd.er, 10000) > library(coda) Loading required package: lattice > summary(rd.mc) Length Class Mode 1 merMCMC S4 > HPDinterval(rd.mc) Error in UseMethod("HPDinterval") : no applicable method for "HPDinterval" > str(rd.mc) Formal class 'merMCMC' [package "lme4"] with 9 slots ..@ Gp : int [1:2] 0 27 ..@ ST : num [1, 1:10000] 1.179 0.878 0.864...

...with this & my other questions.) Anyway, I was trying this to look at the significance of my fixed effects: A6post <- mcmcsamp(A6mlm, 50000) library(coda) HPDinterval(A6post) ..but I got this message: "no applicable method for 'HPDinterval' applied to an object of class "merMCMC"" Should I be coercing A6post to another type, or am I missing other steps altogether? Thanks :) Doug Adams ----- Doug Adams MStat Student University of Utah -- View this message in context: http://n4.nabble.com/lmer-mcmcsamp-coda-HPDinterval-tp1457803p1457803.html Sent from the R h...

...d why the mcmcsamp returns the error for this data set. Even when I change the model and the mcmcsamp appears to run, the output is not as expected: > fm2 <- lmer(Reaction ~ Days + (1|Subject), sleepstudy) > sm2 <- mcmcsamp(fm2, 5000) > summary(sm2) Length Class Mode 1 merMCMC S4 > str(sm2) Formal class 'merMCMC' [package "lme4"] with 9 slots ..@ Gp : int [1:2] 0 18 ..@ ST : num [1, 1:5000] 1.198 0.932 0.835 0.826 0.933 ... ..@ call : language lmer(formula = Reaction ~ Days + (1 | Subject), data = sleepstudy) ..@ deviance: n...

...Shrub (%shrub cover) and Width (width of road), and random effect Site (nested within Site Cluster). >From reading answers to previous posts, it seems that the consensus is to derive p-values using the neat little piece of code posted by Doug Bates as "mcmcpvalue". This code calls the merMCMC object created by the function mcmcsamp, but I can't even get as far as using this function without running into difficulty. Basically, I get an error message saying "Error in .local(object, n, verbose, ...) : Update not yet written" - see below for complete code. Does anyone know wh...

...elp me with the following, I'm having problems accessing the random effect samples following the example on MCMCsamp: (fm1 <- lmer(Reaction ~ Days + (1|Subject) + (0+Days|Subject), sleepstudy)) set.seed(101); samp0 <- mcmcsamp(fm1, n = 1000, saveb=TRUE) str(samp0) Formal class 'merMCMC' [package "lme4"] with 9 slots ..@ Gp : int [1:3] 0 18 36 ..@ ST : num [1:2, 1:1000] 0.98 0.234 1.097 0.258 0.915 ... ..@ call : language lmer(formula = Reaction ~ Days + (1 | Subject) + (0 + Days | Subject), data = sleepstudy) ..@ deviance: num [1:1000...