Skip to contents
BVdk_ML_varCov_estimators()
Maximum Likelihood estimation of the variance of the unknown density variance estimator in an admixture model
BVdk_contrast()
Contrast as defined in Bordes & Vandekerkhove (2010)
BVdk_contrast_gradient()
Gradient of the contrast as defined in Bordes & Vandekerkhove (2010)
BVdk_estimParam()
Estimation of the parameters in a two-component admixture model with symmetric unknown density
BVdk_varCov_estimators()
Estimation of the variance of the estimators in admixture models with symmetric unknown density.
IBM_2samples_test()
Equality test of unknown component distributions in two admixture models with IBM approach
IBM_empirical_contrast()
Empirical computation of the contrast in the Inversion - Best Matching (IBM) method
IBM_estimProp()
Estimate the weights related to the proportions of the unknown components of the two admixture models
IBM_estimVarCov_gaussVect()
Nonparametric estimation of the variance-covariance matrix of the gaussian vector in IBM approach
IBM_gap()
Difference between the unknown empirical cumulative distribution functions in two admixture models
IBM_greenLight_criterion()
Green-light criterion to decide whether to perform full equality test between unknown components between two admixture models
IBM_hessian_contrast()
Hessian matrix of the contrast function in the Inversion - Best Matching (IBM) method
IBM_k_samples_test()
Equality test of unknown component distributions in K admixture models, with IBM approach
IBM_tabul_stochasticInteg()
Distribution of the contrast in the Inversion - Best Matching (IBM) method
IBM_theoretical_contrast()
Theoretical contrast in the Inversion - Best Matching (IBM) method
IBM_theoretical_gap()
Difference between unknown cumulative distribution functions of admixture models at some given point
PatraSen_cv_mixmodel()
Cross-validation estimate (by Patra and Sen) of the unknown component weight as well as the unknown distribution in an admixture model
PatraSen_density_est()
Compute the estimate of the density of the unknown component in an admixture model
PatraSen_dist_calc()
Compute the distance to be minimized using Patra and Sen estimation technique in admixture models
PatraSen_est_mix_model()
Estimate by Patra and Sen the unknown component weight as well as the unknown distribution in admixture models
admix_clustering()
Clustering of K populations following admixture models
admix_estim()
Estimate the unknown parameters of the admixture model(s) under study
admix_test()
Hypothesis test between unknown components of the admixture models under study
allGalaxies
Four galaxies (Carina, Sextans, Sculptor, Fornax) measurements of heliocentric velocities from SIMBAD astronomical database
decontaminated_cdf()
Provide the decontaminated cumulative distribution function (CDF) of the unknown component in an admixture model
decontaminated_density()
Provide the decontaminated density of the unknown component in an admixture model.
detect_support_type()
Detect the support of the random variables under study
estimVarCov_empProcess()
Variance-covariance matrix of the empirical process in an admixture model
gaussianity_test()
One-sample gaussianity test in admixture models using Bordes and Vandekerkhove estimation method
is_equal_knownComp()
Test for equality of the known components between two admixture models
kernel_cdf()
Kernel estimation
kernel_density()
Kernel estimation
knownComp_to_uniform()
Transforms the known component of the admixture distribution to a Uniform distribution
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).
orthoBasis_coef()
Compute expansion coefficients in a given orthonormal polynomial basis.
orthoBasis_test_H0()
Equality test of unknown components between two admixture models using polynomial basis expansions
plot(<decontaminated_density> )
Plot the decontaminated density of the unknown component for an estimated admixture model
plot_mixt_density()
Plot the density of some given sample(s) with mixture distributions.
poly_orthonormal_basis()
Build an orthonormal basis to decompose some given probability density function
print(<admix_cluster> )
Results of the clustering algorithm performed over the K populations following admixture models.
print(<admix_estim> )
Print the results of estimated parameters from K admixture models
print(<admix_test> )
Print the results of statistical test for equality of unknown component distributions in admixture models
rsimmix()
Simulation of a two-component mixture model
rsimmix_mix()
Simulation of a two-component gaussian mixture with one component following a two-component gaussian mixture
sim_gaussianProcess()
Simulation of a Gaussian process
stmf_small
Short-term Mortality Fluctuations (STMF) data series, restricted to 6 countries (Belgium, France, Italy, Netherlands, Spain, Germany).
two_samples_test()
Two-samples hypothesis test on the unknown component in admixture models