similar to: Data preparation for MCMCbinaryChange

Dear All, I am trying to graph a simple scatter plot where the x axis is year and the y axis is a percentage (percentage of infant death). Instead of plotting the raw data, I want to plot summary statistics such as mean and median. Here is the problem: the value range of y is between 0 and 1, but since infant death is a rare event, the mean and median is very low (something like 5%), which shows

Dear All, Are there R packages that can estimate survival model with long-term survivors? This is sometimes known as "cure" model or "split-population" model. Thanks. Shige [[alternative HTML version deleted]]

Dear All, When I tried to run the following code (taken from the *spdplyr* package vignettes): library(spdplyr) library(maptools) data(wrld_simpl) worldcorner <- wrld_simpl %>% mutate(lon = coordinates(wrld_simpl)[,1], lat = coordinates(wrld_simpl)[,2]) %>% filter(lat < -20, lon > 60) %>% dplyr::select(NAME) I got the following error messages: Error in (function (cl,

Dear All, Can anyone give me some hints about how to set starting values for a lmer model? For complicated models like this, good starting values can help the numerical computation and make the model converge faster. Thanks! Shige [[alternative HTML version deleted]]

Dear Colleagues, In the following simple ggplot2 code: -------------------------------- m <- ggplot(d.fig, aes(time, prob)) m + stat_summary(fun.data = "median_hilow", conf.int = .95, geom = "smooth") + facet_wrap(~ Cohort, nrow=1) + coord_cartesian(ylim = c(0, .03)) -------------------------------- Is there a way to replace the y-axis label from "prob" to

Dear All, What is the preferred way to get Bayesian analysis results (such as those from MCMCpacki, MCMCglmm, and DPpackage) into LaTeX table automatically? I have been using the "apsrtable" package and similar functions in "memisc" package, but neither seems to handle MCMC output directly. Many thanks. Shige

Dear All, I am trying to compile&install the package "RGtk2" on my Ubuntu 10.04 box. I did not have problem with earlier versions, but with the new version, I got the following error message : ------------------------------------------------------------------------------------------------- * installing *source* package ?RGtk2? ... checking for pkg-config... /usr/bin/pkg-config

Dear All, I am trying to compile&install the package "RGtk2" on my Ubuntu 10.04 box. I did not have problem with earlier versions, but with the new version, I got the following error message : ------------------------------------------------------------------------------------------------- * installing *source* package ?RGtk2? ... checking for pkg-config... /usr/bin/pkg-config

Dear All, Is there a way to present results from multiple models in one LaTeX table? I did some google search and found out that xtable cannot automate this process (https://stat.ethz.ch/pipermail/r-help/2006-August/111174.html), are there other alternatives? What about Design and Hmisc? Thanks. Best, Shige

Dear All, I have been using Sweave (mainly via the Sweave.sh script) and really like it. I am working a paper (using Sweave, of course) which includes several time-consuming computations, and it gets tedious to re-compile the whoel thing every time I made changes. Then I discover the "cacheSweave" package, which seems the right solution to my problem. I only have on problem. Here is

Dear All, After playing with lmer for couple of days, I have to say that I am amazed! I've been using quite some multilevel/mixed modeling packages, lme4 is a strong candidate for the overall winner, especially for multilevel generzlized linear models. Now go back to my two-level poisson model with cross-classified model. I've been testing various different model specificatios for the

Actually, I re-read the post and think it needs clarification. We may both be right. If the question is "I am building a model and want to know if I should retain this random effect?" (or something like that) then the LRT should be used to compare the fitted model against another model. This would be accomplished via anova(). In other multilevel programs, the variance components are

I'm completely new to R and am trying to install an add-on package for one of our faculty members. I've had no problems with most of them, but am completely stuck trying to figure out why MCMCpack won't install.. any help is VERY much appreciated!!! here's what I get when I try to install the package: * Installing *source* package 'MCMCpack' ... checking for C++ compiler

I installed R-2.3.1 and ran make check without problem, but I am having trouble installing several packages using gcc (GCC) 3.2.3 20030502 (Red Hat Linux 3.2.3-53) on Red Hat Enterprise Linux AS release 3 (Taroon Update 7) Kernel 2.4.21-40.ELsmp on an x86_64 Below are the messages from MCMCpack. Perhaps my systems are messed up? Paul Gilbert > install.packages("MCMCpack")

I'm having some problems in installing some source packages under linux. As an example, MCMCpack. An error is raised when linking: > install.packages("MCMCpack") [...] * Installing *source* package 'MCMCpack' ... checking for C++ compiler default output file name... a.out checking whether the C++ compiler works... yes checking whether we are cross compiling... no checking

Dear All I try to use your R package MCMCpack and I have encountered the following problem: The following code works fine: library(MCMCpack) line <- list(X = c(-2,-1,0,1,2), Y = c(1,3,3,3,5)) posterior1 <- MCMCregress(X~Y, data=line) summary(posterior1) But as long as I try the following lines library(MCMCpack) line <- list(X = c(-2,-1,0,1,2), Y = c(1,3,3,3,5))

Hi list, I tried to install MCMCpack to R-2.12.0, got the following error, CC -m64 -library=stlport4 -I/apps/sparcv9/R-2.12.0/lib/R/include -DSCYTHE_COMPILE_DIRECT -DSCYTHE_DEBUG=0 -DHAVE_TRUNC -DHAVE_IEEEFP_H -I/opt/csw/include -KPIC -g -c MCMCSVDreg.cc -o MCMCSVDreg.o "error.h", line 598: Error: The function "abort" must have a prototype.

Dear R users, Thanks in advance. I am Deb, Statistician at NSW Department of Commerce, Sydney. I am using R 2.9.1 on Windows XP. This has reference to the package “MCMCpack”. My objective is to select a better model using various alternatives. I have provided here an example code from MCMCpack.pdf. The matrix of Bayes Factors is: model1 model2 model3 model1 1.000 14.08

Dear All, With kind help from several friends on the list, I am getting close. Now here are something interesting I just realized: for random effects, lmer reports standard deviation instead of standard error! Is there a hidden option that tells lmer to report standard error of random effects, like most other multilevel or mixed modeling software, so that we can say something like "randome

Hello Everyone Both the MCMCpack and the bayesm libraries allow us to make draws from the Inverse Wishart distribution. But I wanted to find out how exactly is the Inverse Wishart distribution parameterized in these libraries. The reason I ask is the following: Now its generally standard to express Inverse Wishart as IW(0.5 * DOF,0.5* Scale). (DOF-> Degree of freedom, Scale -> Scale