![]() ![]() Let's explore the model fit by hand: there's only one explicit parameter (the among-state standard deviation). Look more carefully: mf <- transform(ame(stdz.model), t <- dredge(stdz.model,trace=TRUE)Īnd try it out: test1 <- lmer(formula = yld.res ~ z.brk + z.onset + (1 | state), Let's find one of the models that breaks: options(warn=1) No huge pairwise correlations among predictors: cor(as.matrix(dd)) Look at coefficients of standardized model: library(dotwhisker)ĭwplot(stdz.model)+geom_vline(xintercept=0,lty=2) Not much going on here, but also nothing too bizarre-looking. Ggplot(mm,aes(value,yld.res,colour=state))+geom_point()+įacet_wrap(~variable,scale="free")+geom_smooth(method="lm") Global.model <- lmer(yld.res ~ rain + brk+ act + onset +Ĭheck out data: library(ggplot2) theme_set(theme_bw()) Replicating your setup: dd <- read.csv("SOtmpdat.csv") The likelihood curve is completely flat at the edge of the estimated space, which is screwing up the convergence checks (this is unusual, but there's nothing wrong with it). I don't see anything fishy in the data or the models. Model failed to converge: degenerate Hessian with 1 negative eigenvaluesģ: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :Ĥ: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :ĥ: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :Ħ: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :ħ: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :Ĩ: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, : Fixed term is "(Intercept)"ġ: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, :Ģ: In checkConv(attr(opt, "derivs"), opt$par, ctrl = control$checkConv, : Any help or suggestion would be appreciated. dredge works fine if I use yld as response. For clarification, yld.res is residual that are obtained from the linear regression of yld against year for each state. I get the following error which I do not know why is happening. Stdz.model <- standardize(global.model,standardize.y = FALSE) Onset + wid + (1|state),data=dat,REML=FALSE) Global.model<-lmer(yld.res ~ rain + brk+ act + I constructed a global model: options(na.action = "na.fail") I am getting some error from the MuMIn::dredge function in R and do not know how to solve it. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |