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‎DESCRIPTION‎

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Type: Package
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Package: melt
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Title: Multiple Empirical Likelihood Tests
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Version: 1.11.3
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Version: 1.11.4
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Authors@R: c(
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person("Eunseop", "Kim", , "[email protected]", role = c("aut", "cph", "cre")),
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person("Steven", "MacEachern", role = c("ctb", "ths")),

‎NEWS.md‎

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# melt 1.11.4
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## MINOR IMPROVEMENTS
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* The internal pseudo-random number generator has been switched from Xoshiro256+ to Xoshiro256++ with the release of the new dqrng package.
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# melt 1.11.3
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## NEW FEATURES
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* New `"ael"` option has been added in the `calibrate` argument of `elt()` for adjusted empirical likelihood calibration.

‎codemeta.json‎

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"codeRepository": "https://github.com/ropensci/melt",
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"issueTracker": "https://github.com/ropensci/melt/issues",
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"license": "https://spdx.org/licenses/GPL-2.0",
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"version": "1.11.3",
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"version": "1.11.4",
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"programmingLanguage": {
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"@type": "ComputerLanguage",
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"name": "R",
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"url": "https://r-project.org"
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},
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"runtimePlatform": "R version 4.3.3 (2024-02-29)",
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"runtimePlatform": "R version 4.4.0 (2024-04-24)",
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"provider": {
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"@id": "https://cran.r-project.org",
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"@type": "Organization",
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},
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"SystemRequirements": null
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},
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"fileSize": "367508.966KB",
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"fileSize": "367660.597KB",
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"citation": [
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{
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"@type": "ScholarlyArticle",

‎cran-comments.md‎

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## Test environments
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* local Arch Linux x86_64, R 4.3.3
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* local Arch Linux x86_64, R 4.4.0
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## R CMD check results
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0 errors | 0 warnings | 1 note
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❯ checking installed package size ... NOTE
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installed size is 155.1Mb
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installed size is 166.2Mb
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sub-directories of 1Mb or more:
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libs 153.5Mb
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libs 164.6Mb
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## revdepcheck results
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‎src/compute_bootstrap_calibration.cpp‎

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x0_fn = transform_x_fn(method);
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const Eigen::MatrixXd g0 = g_fn(x0_fn(x, par, est), par);
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// initialize seed
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dqrng::xoshiro256plus gen(seed);
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dqrng::xoshiro256plusplus gen(seed);
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// discrete uniform distribution
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boost::random::uniform_int_distribution<> u(0, g0.rows() - 1);
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// bootstrap statistics
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{
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#endif
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// make thread local copy of gen
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dqrng::xoshiro256plus lgen(gen);
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dqrng::xoshiro256plusplus lgen(gen);
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#ifdef _OPENMP
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// advance gen by 1 ... nthreads jumps
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lgen.jump(omp_get_thread_num() + 1);

‎vignettes/article.Rnw‎

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difference between two sample means and the difference between two smoothed
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Huber estimators. The \pkg{elhmc} package \citep{elhmc} contains a single
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function \fct{ELHMC} for Hamiltonian Monte Carlo sampling in Bayesian EL
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computation \citep{chaudhuri2017hamiltonian}. The \pkg{ELCIC} package
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\citep{ELCIC} develops an EL-based consistent information criterion in a model
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selection framework. In a broader context of GMM and generalized empirical
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likelihood \citep{smith1997alternative}, a few packages can be used for
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estimation with EL. The \pkg{gmm} package \citep{gmm} provides flexibility in
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specifying moment conditions. Other than GMM and EL, continuous updating
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\citep{hansen1996finite} and several estimation methods that belong to the
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family of generalized empirical likelihood are available. The \pkg{gmm} package
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has been superseded by the \pkg{momentfit} package \citep{momentfit}, which adds
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exponential tilting \citep{kitamura1997information} estimation and methods for
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constructing two-dimensional confidence regions.
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computation \citep{chaudhuri2017hamiltonian}. In a broader context of GMM and
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generalized empirical likelihood \citep{smith1997alternative}, a few packages
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can be used for estimation with EL. The \pkg{gmm} package \citep{gmm} provides
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flexibility in specifying moment conditions. Other than GMM and EL, continuous
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updating \citep{hansen1996finite} and several estimation methods that belong to
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the family of generalized empirical likelihood are available. The \pkg{gmm}
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package has been superseded by the \pkg{momentfit} package \citep{momentfit},
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which adds exponential tilting \citep{kitamura1997information} estimation and
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methods for constructing two-dimensional confidence regions.
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This paper presents the \proglang{R} package \pkg{melt} \citep{melt} that
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performs multiple empirical likelihood tests for regression analysis. The
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seed for random number generation. It defaults to a random integer generated
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from \({1}\) to the maximum integer supported by \proglang{R} on the machine,
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which is determined by \fct{set.seed}. For fast parallel random number
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generation and compatibility with \pkg{OpenMP}, the Xoshiro256+ pseudo-random
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generation and compatibility with \pkg{OpenMP}, the Xoshiro256++ pseudo-random
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number generator (period \({2^{256}} - {1}\)) of \citet{blackman2021scrambled}
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is used internally with the \pkg{dqrng} package \citep{dqrng}.
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

‎vignettes/references.bib‎

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@Manual{dqrng,
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title = {\pkg{dqrng}: Fast Pseudo Random Number Generators},
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author = {Ralf Stubner},
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year = {2023},
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note = {\proglang{R} package version 0.3.2},
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year = {2024},
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note = {\proglang{R} package version 0.4.0},
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url = {https://CRAN.R-project.org/package=dqrng},
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}
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url = {https://CRAN.R-project.org/package=EL},
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}
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@Manual{ELCIC,
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title = {\pkg{ELCIC}: The Empirical Likelihood-Based Consistent Information Criterion},
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author = {Biyi Shen and Ming Wang},
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year = {2023},
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note = {\proglang{R} package version 0.2.1},
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url = {https://CRAN.R-project.org/package=ELCIC},
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}
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@Manual{elhmc,
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title = {\pkg{elhmc}: Sampling from a Empirical Likelihood Bayesian Posterior of Parameters Using Hamiltonian Monte Carlo},
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author = {Dang Trung Kien and Sanjay Chaudhuri and Neo Han Wei},
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title = {\pkg{emplik}: Empirical Likelihood Ratio for Censored/Truncated Data},
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author = {Mai Zhou},
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note = {\proglang{R} package version 1.3.1},
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note = {\proglang{R} package version 1.3-1},
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url = {https://CRAN.R-project.org/package=emplik},
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}
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title = {\pkg{melt}: Multiple Empirical Likelihood Tests},
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author = {Eunseop Kim},
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year = {2024},
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note = {\proglang{R} package version 1.11.3},
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note = {\proglang{R} package version 1.11.4},
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url = {https://CRAN.R-project.org/package=melt},
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}
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author = {{\proglang{R} Core Team}},
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organization = {\proglang{R} Foundation for Statistical Computing},
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address = {Vienna, Austria},
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year = {2023},
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year = {2024},
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url = {https://www.R-project.org/},
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}

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