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Commit0d5e112

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‎DESCRIPTION‎

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Package: xnet
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Type: Package
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Title: Two-Step Kernel Ridge Regression for Network Predictions
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Version: 0.1.10
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Version: 0.1.11
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Authors@R: c(person("Joris","Meys", email = "Joris.Meys@UGent.be", role
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= c("cre","aut")), person("Michiel", "Stock", email =
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"Michiel.Stock@UGent.be", role = "aut"))
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Description: Fit a two-step kernel ridge regression model for
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predicting edges in networks, and carry out cross-validation
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using shortcuts for swift and accurate performance assessment
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(Stock et al, 2018 <doi:10.1093/bib/bby095> ).
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Date:2019-12-09
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Date:2020-02-03
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BugReports: https://github.com/CenterForStatistics-UGent/xnet/issues
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URL: https://github.com/CenterForStatistics-UGent/xnet
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Depends: R(>= 3.4.0)
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Imports: methods, utils, graphics, stats, grDevices
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License: GPL-3
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Encoding: UTF-8
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LazyData: true
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RoxygenNote: 7.0.0
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RoxygenNote: 7.0.2
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Suggests: testthat, knitr, rmarkdown, ChemmineR, covr, fmcsR
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VignetteBuilder: knitr
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Collate: 'Class_linearFilter.R' 'all_generics.R' 'Class_permtest.R'

‎NEWS.md‎

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##xnet 0.1.11
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###Bug fixes
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* unnecessary mentions of dots argument removed from some help pages.
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*`linear_filter()` takes floating point errors into account when checking whether the alpha values sum to 1.
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##xnet 0.1.10
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###Breaking changes

‎R/getters_tskrrImpute.R‎

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#'
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#' @param x a \code{\link[xnet:tskrrImpute-class]{tskrrImpute}} object or
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#' an object inheriting from \code{tskrrImpute}.
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#' @param ... arguments passed to other methods.
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#'
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#' @return For \code{has_imputed_values}: a logical value indicating whether
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#' the model has imputed values. If \code{x} is not some form of a

‎R/getters_tskrrTune.R‎

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#'
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#' @param x a \code{\link[xnet:tskrrTune-class]{tskrrTune}} object or an
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#' object inheriting from \code{tskrrTune}.
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#' @param ... arguments passed to other methods.
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#'
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#' @return For \code{is_tuned}: a logical value indicating whether the
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#' model is tuned.

‎R/linear_filter.R‎

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alpha<- rep(alpha,4)
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elseif(length(alpha)!=4)
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stop("alpha should be a numeric vector with either 1 or 4 values.")
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if(sum(alpha)!=1 )
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stop("alpha values should add up to 1.")
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# Needed to avoid floating point errors when long double disabled
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# Per check by BDR using R configured with --disable-long-double
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if(abs(sum(alpha)-1)>.Machine$double.eps^0.5||
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any(alpha>1)|| any(alpha<0) )
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stop("alpha values should be numbers between 0 and 1 and add up to 1.")
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cm<- colMeans(y,na.rm=na.rm)
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rm<- rowMeans(y,na.rm=na.rm)

‎R/weights.R‎

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#' @param object a \code{\link{tskrr}} object for which the weights
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#' have to be calculated.
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#'
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#' @param ... other arguments passed to methods.
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#'
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#' @return a matrix with the weights for the tskrr model.
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#'

‎man/getters-tskrrImpute.Rd‎

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‎man/getters-tskrrTune.Rd‎

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‎man/weights.Rd‎

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‎tests/testthat/test_linearFilter_calculations.R‎

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expect_error(linear_filter(X,alpha= c(0.5,0.5)),
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"alpha should .* either 1 or 4 values")
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expect_error(linear_filter(X,alpha= c(0.1,0.1,0.1,0.1)),
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"alpha values should add up to 1")
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"alpha values should .* add up to 1")
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expect_error(linear_filter(X,alpha= c(-0.2,0.2,0.5,0.5)),
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"alpha values should be numbers between 0 and 1")
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})

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