After all the positive comments, I would like to raise some concern about some of the non-standard R packages. I have twice experienced a serious error in R packages (not a bug, an error in the algorithm). The authors of the first one did not reply; the authors of the second one said they know about it but do not have the time to fix it. I wonder how many — especially of the PhD/postdoc written packages, which I am sure work for their project — are really working correctly in all situations? Not all of them work on their packages as hard and great work as e.g. D. Bates with his lme4 (GLMM) package, and he and users still discover bugs and flaws in it. I do not want to criticize R; I am using it and I believe that the core packages are as valid as from commercial software (or better). But as I said, I have doubts …
After all the positive comments, I would like to raise some concern about some of the non-standard R packages. I have twice experienced a serious error in R packages (not a bug, an error in the algorithm). The authors of the first one did not reply; the authors of the second one said they know about it but do not have the time to fix it. I wonder how many — especially of the PhD/postdoc written packages, which I am sure work for their project — are really working correctly in all situations? Not all of them work on their packages as hard and great work as e.g. D. Bates with his lme4 (GLMM) package, and he and users still discover bugs and flaws in it. I do not want to criticize R; I am using it and I believe that the core packages are as valid as from commercial software (or better). But as I said, I have doubts about some hardly used ones.
> find(“nls”)
[1] “package:stats”
Official R packages (Base and Recommended)
base, boot, class, cluster, codetools, datasets, foreign, graphics, grDevices, grid, KernSmooth, lattice, MASS, methods, mgcv, nlme, nnet, rpart, spatial, splines, stats, stats4, survival, tcltk, tools, utils
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