similar to: Version 1.0-1 of bayesm

Folks- a patch release of bayesm, v0.0-1, is now available on CRAN. This release corrects some errors in the help pages as well as one error in the function rhierLinearModel involving an incorrect default prior setting. peter ................................ Peter E. Rossi Joseph T. and Bernice S. Lewis Professor of Marketing and Statistics Editor, Quantitative Marketing and Economics Rm

Version 1.1-0 of bayesm is now available on CRAN. This version includes Bayesian inference for the NBD(Poisson) regression model and a hierarchical version of the same. It also includes an additional dataset with count data and various covariates. Comments and suggestions for improvement are most welcome. ................................ Peter E. Rossi Joseph T. and Bernice S. Lewis

Folks- a patch release of bayesm, v0.0-1, is now available on CRAN. This release corrects some errors in the help pages as well as one error in the function rhierLinearModel involving an incorrect default prior setting. peter ................................ Peter E. Rossi Joseph T. and Bernice S. Lewis Professor of Marketing and Statistics Editor, Quantitative Marketing and Economics Rm

Version 1.1-0 of bayesm is now available on CRAN. This version includes Bayesian inference for the NBD(Poisson) regression model and a hierarchical version of the same. It also includes an additional dataset with count data and various covariates. Comments and suggestions for improvement are most welcome. ................................ Peter E. Rossi Joseph T. and Bernice S. Lewis

We are pleased to announce the release of version 0.0 of bayesm on CRAN. bayesm covers many important models used in marketing and micro-econometrics applications. The package includes: Bayes Regression (univariate or multivariate dep var) Multinomial Logit Multinomial and Multivariate Probit Multivariate Mixtures of Normals Hierarchical Linear Models with a normal prior and covariates

We are pleased to announce the release of version 0.0 of bayesm on CRAN. bayesm covers many important models used in marketing and micro-econometrics applications. The package includes: Bayes Regression (univariate or multivariate dep var) Multinomial Logit Multinomial and Multivariate Probit Multivariate Mixtures of Normals Hierarchical Linear Models with a normal prior and covariates

Dear r-help- >From reading the CRAN web page, it appears that you should not submit precompiled binary versions of your package, but rather that these are built for you by someone working with CRAN. I submitted my package using R CMD build but without the binary flag on. I'd like to have a binary version available for Windows users. Should I submit a precompiled binary version as well?

Folks- I have developed a package which I am planning on posting to CRAN. I include examples for each of the 40 or so functions in the package. However, since the examples are non-trivial and the package is using MCMC simulation methods, it takes about 20 minutes to run the complete set of examples on a 2.8 Ghz windows PC. The R process reaches a high water mark of about 100 MB of memory as

Folks- We are pleased to announce the release of version 2.0-1 of bayesm. Highlights of the new version: 1. Bayesian treatment of SUR (seemingly unrelated regression) 2. Added clustering to mixture of normals models 3. Added routines to compute implied univ and bivariate densities from mixture of normals MCMC draws 4. improved input error checking in many routines please get rid of your

bayesm version 2.2-0 is now available on CRAN. Major changes include: 1. general density estimation using a Dirichlet Process Prior and a normal base 2. linear instrumental variable models with unknown error distributions (the Bayesian analogue of IV methods). Achieved via DP priors. peter r ................................ Peter E. Rossi Joseph T. and Bernice S. Lewis Professor of

Folks- We are pleased to announce the release of version 2.0-1 of bayesm. Highlights of the new version: 1. Bayesian treatment of SUR (seemingly unrelated regression) 2. Added clustering to mixture of normals models 3. Added routines to compute implied univ and bivariate densities from mixture of normals MCMC draws 4. improved input error checking in many routines please get rid of your

I can successfully "check" a package with source under 2.5.1, including compiling source files and running examples with no errors or warnings. when I try with R2.6.2, I get make errors: making bayesmc.d from bayesmc.c make[3]:gcc-sjlj: Command not found etc. my gcc is version 3.4.2 I'm using Windows XP. Any thoughts? thanks! peter r ................................ Peter

Release 2.1-1 is now available on CRAN. This release includes-- bayesm classes (some compatible with the mcmc class of coda) for output. plot and summary methods for these classes. additional datasets including store-level panel data. peter r ................................ Peter E. Rossi Joseph T. and Bernice S. Lewis Professor of Marketing and Statistics Editor, Quantitative Marketing

I have developed a package, bayesm, which uses existing classes of objects. I would like to add a new class corresponding to objects from this package. I have been reading about classes and all sources tell me that I should use so-called "new" or S4 classes. However, a major purpose of defining a class for my package would be to add methods to the existing generic functions: print,

I have a set of n vectors, x_1, ..., x_n, of the same length. I would like to form the vector of dot products -- x_1'x_1, ..., x_n'x_n the fastest way I can think to do this is to put the vectors into a matrix and do diag(crossprod(X)) however, this seems to be very wasteful since this computes n(n+1)/2-n unnecessary dot products. Is there a better way using existing functions in R?

Writing R Ext says to treat R objects that are arguments to .Call as read only (i.e. don't modify). I have a long list of lists that and I want to avoid the overhead of a copy in my C code. I would just like to modify some of the elements of list by replacing them with elements of exactly the same size/type. below is an example of the essence of the problem. This seems to work. Is this

I have noticed dramatic differences in the run-time for the execution of one of my functions depending on whether or not R was restarted. Immediately after restart of R GUI, exec time = 2.8 min. If I then repeat the execution of the function in the same R session, exec time = 7.1 min. Removing all objects via rm(list=(all=TRUE)) and initiating gc (gc(reset=TRUE)) helps, but only slightly (exec

To whom it may concern, I am trying to maximize a log-likelihood function using optim. This is a simple problem with only 18 parameters. To conserve memory, I am using sparse matrices (SLAM) for some of the data matrices used in the computation of the likelihood. However, optim appears to convert the sparse matrix back to regular data format. This causes me to run out of memory as R tries to

Dear all: I'm enjoying using rgl and I want to set a specific viewpoint. I understand that view3d() will do so by setting the 3d polar coordinate angles, theta and phi. In standard polar coordinates, theta is the angle away from the X axis in the X-Y plane and phi (inclination angle) is the angle between the Z axis and the radius vector It appears that when you use view3d() theta is

Version 2.0-2 of bayesm is available on CRAN. This version includes bug fixes for rhierMnlRwMixture and rhierLinearModel. peter rossi _______________________________________________ R-packages mailing list R-packages at stat.math.ethz.ch https://stat.ethz.ch/mailman/listinfo/r-packages