https://github.com/cran/clusterGeneration
Tip revision: 9686937c56456e00dc9e3adf41bb8fd8cfa718b3 authored by Weiliang Qiu on 16 August 2023, 04:20:02 UTC
version 1.3.8
version 1.3.8
Tip revision: 9686937
NEWS
clusterGeneration v1.3.8 (creation date: 2023-08-15)
=================
Changes:
* (1) fixed a bug in genMeanCov(): commented out for loop about 'eg'
* (2) fixed a bug in findNeighbors(): 'pos <- which(tmp < -1 || tmp > 1)'
* should be 'pos <- which(tmp < -1 | tmp > 1)'
* (3) fixed format in NEWS file
* (4) fixed the bug 'Escaped LaTeX specials: \_' in Rd files
clusterGeneration v1.3.7 (creation date: 2020-12-12)
=================
Changes:
* (1) added function "genOrthogonal" to export list
clusterGeneration v1.3.6 (creation date: 2020-11-21)
=================
Changes:
* (1) added "na.rm=TRUE" when calling 'sum', 'max'
* (2) when call a function, explicitly call its input
* (3) fixed a bub in function 'genMeanCov': when calling 'genPositiveDefMat', the input 'eigenvalue' was missing.
* (4) added input argument 'eigenvalue' to function 'genMeanCov' and 'genRandomClust' and 'genNoisyMeanCov' and 'simClustDesign'
clusterGeneration v1.3.5 (creation date: 2020-10-03)
=================
Changes:
* (1) add new argument "eigenvalue" so that user can supply own eigenvalues for algorithm covMethod=c("eigen")
* (2) in genPositiveDefMat, using crossprod(Q * sqrt(egvalues)) instead of Sigma <- Q %*% u %*% t(Q) leads to nice improvements (3-4 times faster) when simulating large matrices (dim>500). Reason is that the new code does not require to form the u matrix, and that crossprod() is quite faster when used with a single argument (exploiting that output will be symmetric)
* Thanks Dr. Matthieu Stigler (matthieu.stigler@gmail.com) for these 2 suggestions!
* (3) change maintainer's email address to <weiliang.qiu@gmail.com>
clusterGeneration v1.3.2 (creation date: 2015-02-14)
=================
Changes:
* (1) fixed a few bugs in function 'getSepProjData':
* 'u.cl <- unique(cl)' should be
* 'u.cl <- sort(unique(cl)'
* 'yi <- y[cl == u.cl[i], , drop = FALSE]'
* should be
* 'yi <- y[which(cl == u.cl[i]), , drop = FALSE]'
clusterGeneration v1.3.1 (creation date: 2013-01-07)
=================
Changes:
* (1) added a space between 'Weiliang Qiu' and
* '<stwxq@channing.harvard.edu>' in the 'Maintainer' slot
* in the DESCRIPTION file
* Thank Dr. Kurt Hornik for his kind help!
clusterGeneration v1.3.0 (creation date: 2013-01-06)
=================
Changes:
* (1) rename 'log.txt' file to 'NEWS'.
* Thanks for Mr. Suraj Gupta (<suraj@wingedfootcapital.com>) for this suggestion!
clusterGeneration v1.2.9 (creation date: 2012-04-02)
=================
Changes:
* (1) fixed a bug pointed by Dr. Anton Korobeynikov
* <anton@korobeynikov.info>
* Dear Dr. Weiliang Qiu,
*
* Recently we tried to used your package clusterGeneration but found
* that the behavior of genRandomClust() with clustszind == 3 is
* definitely wrong compared to the one documented.
* After looking into the implementation it became obvious that
* genMemSize() function does wrong things: it tries to sample from 1:G
* using provided clusterSizes as weights. Surely the output clusters
* have wrong sizes (not the ones specified).
*
* The fix is pretty simple: change the code for clustszind == 3 to
* something like this:
*
* mem <- sample(unlist(lapply(1:G, function(x) rep.int(x, times =
* clustSizes[x]))))
* N <- sum(clustSizes)
*
* Or, maybe if you want to keep the current behavior it'd be better to
* introduce new clustszind variant.
*
*
* (2) add 'clustSizes<-as.integer(clustSizes)' before checking
* '!is.integer(clustSizes[i])'
clusterGeneration v1.2.8 (creation date: 2012-03-19)
=================
Changes:
* (1) fixed a few warning messages:
* (a)>>
* checking R code for possible problems ... NOTE
*genNoisyMeanCov: warning in eigen(Sigma.noisy, sym = TRUE): partial
* argument match of 'sym' to 'symmetric'
* (b)>>>
** running examples for arch 'i386' ... WARNING
*Found the following significant warnings:
* Warning: sd(<matrix>) is deprecated.
* Warning: sd(<matrix>) is deprecated.
* Warning: sd(<matrix>) is deprecated.
* Warning: sd(<matrix>) is deprecated.
*Deprecated functions may be defunct as soon as of the next release of
*R.
*See ?Deprecated.
** running examples for arch 'x64' ... WARNING
*Found the following significant warnings:
*
* Warning: sd(<matrix>) is deprecated.
* Warning: sd(<matrix>) is deprecated.
* Warning: sd(<matrix>) is deprecated.
* Warning: sd(<matrix>) is deprecated.
*Deprecated functions may be defunct as soon as of the next release of
*R.
*See ?Deprecated.
*
* (2) add 'na.rm=TRUE' to functions 'min', 'max', 'sum', 'mean', 'median', etc.