https://github.com/cran/clusterGeneration
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Tip revision: 9686937c56456e00dc9e3adf41bb8fd8cfa718b3 authored by Weiliang Qiu on 16 August 2023, 04:20:02 UTC
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.

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