Package: admix 2.1-3

admix: Package Admix for Admixture (aka Contamination) Models

Implements techniques to estimate the unknown quantities related to two-component admixture models, where the two components can belong to any distribution (note that in the case of multinomial mixtures, the two components must belong to the same family). Estimation methods depend on the assumptions made on the unknown component density (see Bordes and Vandekerkhove (2010) <doi:10.3103/S1066530710010023>; Patra and Sen (2016) <doi:10.1111/rssb.12148>); Milhaud, Pommeret, Salhi and Vandekerkhove (2022) <doi:10.1016/j.jspi.2021.05.010>). In practice, one can estimate both the mixture weight and the unknown component density in a wide variety of frameworks. On top of that, hypothesis tests can be performed in one and two-sample contexts to test the unknown component density (see Milhaud, Pommeret, Salhi, Vandekerkhove (2023)). Finally, clustering of unknown mixture components is also feasible in a K-samples setting.

Authors:Xavier Milhaud [aut, cre], Pierre Vandekerkhove [ctb], Denys Pommeret [ctb], Yahia Salhi [ctb]

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admix.pdf |admix.html✨
admix/json (API)

# Install 'admix' in R:
install.packages('admix', repos = c('https://xaviermilhaud.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/xaviermilhaud/admix/issues

Uses libs:
  • c++– GNU Standard C++ Library v3
Datasets:
  • allGalaxies - Four galaxies (Carina, Sextans, Sculptor, Fornax) measurements of heliocentric velocities from SIMBAD astronomical database
  • milkyWay - Heliocentric velocity measured for the Milky Way (from Walker, M. G., M. Mateo, E. W. Olszewski, O. Y. Gnedin, X. Wang, B. Sen, and M. Woodroofe (2007). Velocity dispersion profiles of seven dwarf spheroidal galaxies. Astrophysical J. 667(1), L53–L56).
  • mortality_sample - Dataset giving exposure-to-death (population size) and number of deaths for males in eleven european countries, with ages ranging from 30 years old to 85 years old.
  • stmf_small - Short-term Mortality Fluctuations (STMF) data series, restricted to 6 countries (Belgium, France, Italy, Netherlands, Spain, Germany).

On CRAN:

40 exports 1 stars 1.47 score 8 dependencies 2 mentions 8 scripts 385 downloads

Last updated 5 months agofrom:dce5cef295. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 23 2024
R-4.5-win-x86_64OKAug 23 2024
R-4.5-linux-x86_64OKAug 23 2024
R-4.4-win-x86_64OKAug 23 2024
R-4.4-mac-x86_64OKAug 23 2024
R-4.4-mac-aarch64OKAug 23 2024
R-4.3-win-x86_64OKAug 23 2024
R-4.3-mac-x86_64OKAug 23 2024
R-4.3-mac-aarch64OKAug 23 2024

Exports:admix_clusteringadmix_estimadmix_testBVdk_contrastBVdk_contrast_gradientBVdk_estimParamBVdk_ML_varCov_estimatorsBVdk_varCov_estimatorsdecontaminated_cdfdecontaminated_densitydetect_support_typeestimVarCov_empProcessgaussianity_testIBM_2samples_testIBM_empirical_contrastIBM_estimPropIBM_estimVarCov_gaussVectIBM_gapIBM_greenLight_criterionIBM_hessian_contrastIBM_k_samples_testIBM_tabul_stochasticIntegIBM_theoretical_contrastIBM_theoretical_gapis_equal_knownCompkernel_cdfkernel_densityknownComp_to_uniformorthoBasis_coeforthoBasis_test_H0PatraSen_cv_mixmodelPatraSen_density_estPatraSen_dist_calcPatraSen_est_mix_modelplot_mixt_densitypoly_orthonormal_basisrsimmixrsimmix_mixsim_gaussianProcesstwo_samples_test

Dependencies:cubaturefdrtoolIsoMASSorthopolynompolynompracmaRcpp

Clustering of unknown subpopulations in admixture models

Xavier Milhaud

Rendered fromadmixture-clustering.Rmdusingknitr::rmarkdownon Aug 23 2024.

Last update: 2023-07-06
Started: 2021-05-28

Estimation of unknown elements in admixture models

Xavier Milhaud

Rendered fromadmixture-weight-estimation.Rmdusingknitr::rmarkdownon Aug 23 2024.

Last update: 2023-03-22
Started: 2021-05-28

Hypothesis test in admixture models

Xavier Milhaud

Rendered fromtest-hypothesis.Rmdusingknitr::rmarkdownon Aug 23 2024.

Last update: 2023-07-11
Started: 2021-05-28

Readme and manuals

Help Manual

Help pageTopics
Clustering of K populations following admixture modelsadmix_clustering
Estimate the unknown parameters of the admixture model(s) under studyadmix_estim
Hypothesis test between unknown components of the admixture models under studyadmix_test
Four galaxies (Carina, Sextans, Sculptor, Fornax) measurements of heliocentric velocities from SIMBAD astronomical databaseallGalaxies
Contrast as defined in Bordes & Vandekerkhove (2010)BVdk_contrast
Gradient of the contrast as defined in Bordes & Vandekerkhove (2010)BVdk_contrast_gradient
Estimation of the parameters in a two-component admixture model with symmetric unknown densityBVdk_estimParam
Maximum Likelihood estimation of the variance of the unknown density variance estimator in an admixture modelBVdk_ML_varCov_estimators
Estimation of the variance of the estimators in admixture models with symmetric unknown density.BVdk_varCov_estimators
Provide the decontaminated cumulative distribution function (CDF) of the unknown component in an admixture modeldecontaminated_cdf
Provide the decontaminated density of the unknown component in an admixture model.decontaminated_density
Detect the support of the random variables under studydetect_support_type
Variance-covariance matrix of the empirical process in an admixture modelestimVarCov_empProcess
One-sample gaussianity test in admixture models using Bordes and Vandekerkhove estimation methodgaussianity_test
Equality test of unknown component distributions in two admixture models with IBM approachIBM_2samples_test
Empirical computation of the contrast in the Inversion - Best Matching (IBM) methodIBM_empirical_contrast
Estimate the weights related to the proportions of the unknown components of the two admixture modelsIBM_estimProp
Nonparametric estimation of the variance-covariance matrix of the gaussian vector in IBM approachIBM_estimVarCov_gaussVect
Difference between the unknown empirical cumulative distribution functions in two admixture modelsIBM_gap
Green-light criterion to decide whether to perform full equality test between unknown components between two admixture modelsIBM_greenLight_criterion
Hessian matrix of the contrast function in the Inversion - Best Matching (IBM) methodIBM_hessian_contrast
Equality test of unknown component distributions in K admixture models, with IBM approachIBM_k_samples_test
Distribution of the contrast in the Inversion - Best Matching (IBM) methodIBM_tabul_stochasticInteg
Theoretical contrast in the Inversion - Best Matching (IBM) methodIBM_theoretical_contrast
Difference between unknown cumulative distribution functions of admixture models at some given pointIBM_theoretical_gap
Test for equality of the known components between two admixture modelsis_equal_knownComp
Kernel estimationkernel_cdf
Kernel estimationkernel_density
Transforms the known component of the admixture distribution to a Uniform distributionknownComp_to_uniform
Heliocentric velocity measured for the Milky Way (from Walker, M. G., M. Mateo, E. W. Olszewski, O. Y. Gnedin, X. Wang, B. Sen, and M. Woodroofe (2007). Velocity dispersion profiles of seven dwarf spheroidal galaxies. Astrophysical J. 667(1), L53–L56).milkyWay
Dataset giving exposure-to-death (population size) and number of deaths for males in eleven european countries, with ages ranging from 30 years old to 85 years old.mortality_sample
Compute expansion coefficients in a given orthonormal polynomial basis.orthoBasis_coef
Equality test of unknown components between two admixture models using polynomial basis expansionsorthoBasis_test_H0
Cross-validation estimate (by Patra and Sen) of the unknown component weight as well as the unknown distribution in an admixture modelPatraSen_cv_mixmodel
Compute the estimate of the density of the unknown component in an admixture modelPatraSen_density_est
Compute the distance to be minimized using Patra and Sen estimation technique in admixture modelsPatraSen_dist_calc
Estimate by Patra and Sen the unknown component weight as well as the unknown distribution in admixture modelsPatraSen_est_mix_model
Plot the density of some given sample(s) with mixture distributions.plot_mixt_density
Plot the decontaminated density of the unknown component for an estimated admixture modelplot.decontaminated_density
Build an orthonormal basis to decompose some given probability density functionpoly_orthonormal_basis
Results of the clustering algorithm performed over the K populations following admixture models.print.admix_cluster
Print the results of estimated parameters from K admixture modelsprint.admix_estim
Print the results of statistical test for equality of unknown component distributions in admixture modelsprint.admix_test
Simulation of a two-component mixture modelrsimmix
Simulation of a two-component gaussian mixture with one component following a two-component gaussian mixturersimmix_mix
Simulation of a Gaussian processsim_gaussianProcess
Short-term Mortality Fluctuations (STMF) data series, restricted to 6 countries (Belgium, France, Italy, Netherlands, Spain, Germany).stmf_small
Two-samples hypothesis test on the unknown component in admixture modelstwo_samples_test