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admix
View on CRAN: Click
here
Download and install admix package within the R console
Install from CRAN:
install.packages("admix")
Install from Github:
library("remotes")
install_github("cran/admix")
Install by package version:
library("remotes")
install_version("admix", "2.1-2")
Attach the package and use:
library("admix")
Maintained by
Xavier Milhaud
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-06-14
Latest Update: 2023-07-12
Description:
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) ;
Patra and Sen (2016) ); Milhaud, Pommeret, Salhi and Vandekerkhove
(2022) ). 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.
How to cite:
Xavier Milhaud (2021). admix: Package Admix for Admixture (aka Contamination) Models. R package version 2.1-2, https://cran.r-project.org/web/packages/admix
Previous versions and publish date:
Other packages that cited admix R package
View admix citation profile
Other R packages that admix depends,
imports, suggests or enhances
Functions, R codes and Examples using
the admix R package
Some associated functions: BVdk_ML_varCov_estimators . BVdk_contrast . BVdk_contrast_gradient . BVdk_estimParam . BVdk_varCov_estimators . IBM_2samples_test . IBM_empirical_contrast . IBM_estimProp . IBM_estimVarCov_gaussVect . IBM_gap . IBM_greenLight_criterion . IBM_hessian_contrast . IBM_k_samples_test . IBM_tabul_stochasticInteg . IBM_test_H0 . IBM_theoretical_contrast . IBM_theoretical_gap . PatraSen_cv_mixmodel . PatraSen_density_est . PatraSen_dist_calc . PatraSen_est_mix_model . admix-package . admix_clustering . admix_estim . admix_test . allGalaxies . decontamin_cdf_unknownComp . decontamin_density_unknownComp . decontaminated_cdf . decontaminated_density . detect_support_type . estimVarCov_empProcess . gaussianity_test . is_equal_knownComp . kernel_cdf . kernel_density . knownComp_to_uniform . milkyWay . orthoBasis_coef . orthoBasis_test_H0 . plot.decontaminated_density . plot_admix . plot_decontamin_cdf . plot_decontamin_density . plot_mixt_density . poly_orthonormal_basis . print.admix_cluster . print.admix_estim . print.admix_test . rsimmix . rsimmix_mix . silhouette_criterion . sim_gaussianProcess . stmf_small . two_samples_test .
Some associated R codes: BVdk_ML_varCov_estimators.R . BVdk_contrast.R . BVdk_contrast_gradient.R . BVdk_estimParam.R . BVdk_varCov_estimators.R . IBM_2samples_test.R . IBM_empirical_contrast.R . IBM_estimProp.R . IBM_estimVarCov_gaussVect.R . IBM_gap.R . IBM_greenLight_criterion.R . IBM_hessian_contrast.R . IBM_k_samples_test.R . IBM_tabul_stochasticInteg.R . IBM_test_H0.R . IBM_theoretical_contrast.R . IBM_theoretical_gap.R . PatraSen_cv_mixmodel.R . PatraSen_density_est.R . PatraSen_dist_calc.R . PatraSen_est_mix_model.R . RcppExports.R . admix-package.R . admix_clustering.R . admix_estim.R . admix_test.R . allGalaxies.R . decontamin_cdf_unknownComp.R . decontamin_density_unknownComp.R . decontaminated_cdf.R . decontaminated_density.R . detect_support_type.R . estimVarCov_empProcess.R . gaussianity_test.R . is_equal_knownComp.R . kernel_cdf.R . kernel_density.R . knownComp_to_uniform.R . milkyWay.R . orthoBasis_coef.R . orthoBasis_test_H0.R . plot.decontaminated_density.R . plot_admix.R . plot_decontamin_cdf.R . plot_decontamin_density.R . plot_mixt_density.R . poly_orthonormal_basis.R . print.admix_cluster.R . print.admix_estim.R . print.admix_test.R . rsimmix.R . silhouette_criterion.R . sim_gaussianProcess.R . stmf_small.R . two_samples_test.R . zzz.R . Full admix package functions and examples
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