Not getting good convergence from jags models with uniformative priors without observation noise and arbitary starting postions. See examples:
- fixed myers_jags run, loads knitr_defaults 11:18 am 2013/05/29
- trouble with MCMC convergence for process-noise-only: Now with longer runs and better posterior estimator. Set for run on zero. 11:01 am 2013/05/29
Also a few updates:
- Combine comment code into single file for both models: comment_reply.Rmd
- Comment resubmitted. (repository tag:
- Ooh: tags provide a convenient way to make readable version-stable links (e.g. as opposed to linking by the hash.)
Separated out my common knitr settings that usually take up space in my first code chunk.
# My preferred defaults (may be changed in individual chunks) opts_chunk$set(tidy=FALSE, warning=FALSE, message=FALSE, cache=TRUE, comment=NA, verbose=TRUE, fig.width=6, fig.height=4) # Name the cache path and fig.path based on filename... opts_chunk$set(fig.path = paste("figure/", gsub(".Rmd", "", knitr:::knit_concord$get('infile')), "-", sep=""), cache.path = paste(gsub(".Rmd", "", knitr:::knit_concord$get('infile') ), "/", sep="")) # Set plotting to bw plot default, but with transparent background elements. # Note transparency requires the panel.background, plot.background, and device background all be set! library(ggplot2) theme_set(theme_bw(base_size=12)) theme_update(panel.background = element_rect(fill = "transparent", colour = NA), plot.background = element_rect(fill = "transparent", colour = NA)) opts_chunk$set(dev.args=list(bg="transparent")) # Set a color-blind friendly pallette # adapted from https://www.cookbook-r.com/Graphs/Colors_(ggplot2)/ cbPalette <- c("#000000", "#E69F00", "#56B4E9", "#009E73", "#F0E442", "#0072B2", "#D55E00", "#CC79A7")
also appears as gist:5600558
Saved script as
~/.knit_defaults.R and is sourced in by the first chunk instead.