similar to: S3 vs S4 classes

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

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

Dear all, I asked this question on r-package-devel but Martin Maechler pointed out this was more suited on R-devel. So here it goes: per the manual, one should create and register both the S3 and a S4 method if one needs a method for an S4 class for a function using S3 dispatching. This is cumbersome, and not very optimal. I was wondering if there's a better way to do this. Currently I

On Thu, May 24, 2018 at 6:20 PM, Michael Lawrence <lawrence.michael at gene.com > wrote: > You only have to make an S4 method if there is already an S4 generic. > If there is just an S3 generic, then just define S3 methods on it. I was refering to the recommendations in ?Methods_for_S3 ( https://stat.ethz.ch/R-manual/R-devel/library/methods/html/Methods_for_S3.html). : "Two

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 1.0-1 of bayesm is now available on CRAN. This is our first "production" version which include s much improved documentation as well as five data sets used in our book, Bayesian Statistics and Marketing. peter r ................................ Peter E. Rossi Joseph T. and Bernice S. Lewis Professor of Marketing and Statistics Editor, Quantitative Marketing and Economics

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 1.0-1 of bayesm is now available on CRAN. This is our first "production" version which include s much improved documentation as well as five data sets used in our book, Bayesian Statistics and Marketing. peter r ................................ Peter E. Rossi Joseph T. and Bernice S. Lewis Professor of Marketing and Statistics Editor, Quantitative Marketing and Economics

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- 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

Dear list, It seems that S4 methods defined for an S3 'base' generic are not used in 'base' functions. This can be problematic when 'base' functions start with something like 'as.matrix'. ### START R code setClass("classA", contains = "matrix", representation(realData = "numeric")) setMethod("as.matrix",

Dear developers, the implementation of S4 generics for existing S3 ones in the base package is concerned to be a threat to quick startup times [1]. But since S4 is promoted, and S3/S4 interoperability a pain when package developing [2], are there efforts to improve the situation? E.g. an S3 free system, etc. A good thing [2] is the package 'stats4', including some setGeneric calls (e.g.

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'd like to have a class A that computes a likelihood, and a subclass B that computes the same likelihood by sometimes throws in an additional term (B includes measurement error). So B's likelihood needs to call A's, and then (sometimes) multiply by an additional term. It sounds as if, in the S3 scheme, NextMethod is supposed to do this: like.A <- function(stuff) compute value

A general goal for the next version of R is to make S4 and S3 play better together. As mentioned in a previous thread, one limitation has been that S3 generic functions, specifically the UseMethod() call, did not make use of S4 inheritance when dispatching on general S4 objects. This has been fixed in a version committed today (updated to rev 52267). The code change is not large, but it