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  "Title": "High-Dimensional Methods for Elliptically Symmetric\nDistributions",
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  "_exports": [
    "acg_loglik",
    "bai_saranadasa_two_sample_test",
    "basic_shape",
    "basics_shape",
    "bickel_levina_covariance_threshold",
    "book_gaussian_alpha_cauchy_test",
    "cai_liu_adaptive_covariance_threshold",
    "cai_liu_xia_two_sample_test",
    "cca_bartlett_test",
    "chen_qin_two_sample_test",
    "chen_song_feng_rank_white_noise_test",
    "chen_zhang_zhong_covariance_test",
    "cheng_sscm_equality_test",
    "chime_clustering",
    "classical_cca",
    "classical_cusum_test",
    "classical_lda_classifier",
    "classical_pca",
    "classical_qda_classifier",
    "clime_precision",
    "composite_t2_two_sample_test",
    "conditional_alpha_sieve_design",
    "conditional_alpha_sieve_fit",
    "conditional_factor_wald_test",
    "dsda_classifier",
    "ec2_covariance",
    "elliptical_factor_number",
    "elliptical_factor_precision",
    "elliptical_oracle_classifier",
    "elliptical_regularized_hotelling_cauchy_test",
    "elliptical_regularized_hotelling_test",
    "erht_change_point_test",
    "erht_wbs",
    "fair_classifier",
    "fantope_pca",
    "feng_jiang_liu_xiong_panel_independence_test",
    "feng_lan_liu_ma_alpha_max_test",
    "feng_liu_ma_white_noise_test",
    "feng_liu_rank_sphericity_test",
    "feng_spatial_rank_proportionality_test",
    "feng_sun_one_sample_test",
    "feng_wang_pdq_two_sample_test",
    "feng_zhang_liu_spatial_rank_test",
    "feng_zou_wang_two_sample_sign_test",
    "feng_zou_wang_zhu_two_sample_test",
    "fisher_sun_gallagher_sphericity_test",
    "gaussian_alpha_combination_test",
    "gaussian_covariance_lrt",
    "gaussian_graphical_lasso",
    "gaussian_lda_oracle",
    "gaussian_mixture_em",
    "gaussian_qda_oracle",
    "gaussian_wilks_independence_test",
    "generalized_sign_pca",
    "generic_weighted_hr_location",
    "gqda_classifier",
    "grs_alpha_test",
    "hallin_paindaveine_shape_test",
    "hd_classifier_fit",
    "high_dimensional_hr",
    "hotelling_one_sample_test",
    "hotelling_two_sample_test",
    "hr_estimator",
    "hr_gqda",
    "hr_qda",
    "if_pca",
    "independence_classifier",
    "inst_one_sample_test",
    "jiang_da_qda",
    "john_sphericity_test",
    "k_spatial_median",
    "kendall_factor_number",
    "kendall_pca",
    "li_chen_covariance_test",
    "li_shao_sparse_qda",
    "li_wang_zou_two_sample_sign_test",
    "linear_pool_covariance",
    "liu_feng_ma_spatial_sign_alpha_test",
    "lloyd_kmeans",
    "lpd_classifier",
    "ma_feng_wang_bao_conditional_alpha_test",
    "ma_lan_su_tsai_conditional_alpha_sum_test",
    "mauchly_sphericity_test",
    "nagao_identity_test",
    "normalize_shape",
    "ollila_raninen_shrinkage_covariance",
    "oracle_weighted_sign_sum_test",
    "park_ayyala_one_sample_test",
    "pesaran_cd_test",
    "pesaran_yamagata_alpha_test",
    "pmd_sparse_cca",
    "pmd_sparse_pca",
    "poet_covariance",
    "poet_tme",
    "regularized_spatial_sign_covariance",
    "relliptical",
    "robust_factor_subspace",
    "robust_gqda",
    "rothman_levina_zhu_covariance_threshold",
    "rspherical",
    "rts_factor",
    "scaled_spatial_median",
    "sdar_qda",
    "semc_fit",
    "semc_select_k_gap",
    "shao_threshold_lda",
    "sign_whitened_sparse_cca",
    "sm_sscm",
    "sparse_k_spatial_median",
    "sparse_kmeans",
    "sparse_kmeans_select_s",
    "sparse_kmedian",
    "sparse_plugin_lda",
    "sparse_plugin_qda",
    "sparse_sm_select_k",
    "sparse_sm_select_tau",
    "sparse_spatial_sign_pca",
    "spatial_kendall",
    "spatial_median",
    "spatial_rank",
    "spatial_rank_covariance",
    "spatial_rank_test",
    "spatial_sign",
    "spatial_sign_change_point_test",
    "spatial_sign_max_test",
    "spatial_sign_maxsum_test",
    "spatial_sign_pca",
    "spatial_sign_poet",
    "spatial_sign_precision",
    "spatial_sign_precision_lda",
    "spatial_sign_sphericity_test",
    "spatial_sign_test",
    "spatial_signed_rank_test",
    "srivastava_du_one_sample_test",
    "srivastava_katayama_kano_two_sample_test",
    "sscca",
    "sscm",
    "sslda",
    "ssqda",
    "tensor_spatial_sign_precision",
    "threshold_spatial_sign_precision",
    "threshold_tensor_spatial_sign_precision",
    "tinst_two_sample_test",
    "truncated_power_pca",
    "tyler_shape",
    "wang_feng_dms_test",
    "wang_liu_feng_ma_serial_panel_test",
    "wang_liu_feng_vector_independence_test",
    "wang_liu_feng_vector_u_independence_test",
    "wang_peng_li_one_sample_test",
    "wang_xu_approx_randomization_test",
    "wang_yao_corrected_john_test",
    "wang_yao_corrected_lrt",
    "wang_zhao_feng_wang_mutual_fund_fdr",
    "weighted_scaled_spatial_median",
    "weighted_spatial_sign_alpha_oracle_test",
    "white_noise_portmanteau_test",
    "xu_lin_wei_pan_aspu_test",
    "yan_zhao_feng_weighted_max_test",
    "yan_zhao_feng_weighted_maxsum_test",
    "zhang_feng_radial_directional_test",
    "zhang_feng_rank_one_sample_test",
    "zhang_feng_rank_two_sample_test",
    "zhang_zhou_guo_linear_hypothesis_test",
    "zhang_zhou_guo_one_sample_test",
    "zhang_zhou_guo_paired_test",
    "zhang_zhu_zhang_two_sample_test",
    "zhao_chen_wang_spatial_sign_white_noise_test",
    "zhao_chen_zi_inst_alpha_test",
    "zhao_conditional_spatial_sign_sum_test",
    "zhao_feng_strongcorr_sign_test",
    "zhao_feng_wang_wang_robust_alpha_test",
    "zhao_wang_conditional_spatial_sign_test",
    "zhao_yang_zhang_feng_wang_adaptive_sphericity_test",
    "zhao_yang_zhang_feng_wang_sign_max_test",
    "zou_peng_feng_wang_sphericity_test"
  ],
  "_help": [
    {
      "page": "acg_loglik",
      "title": "Angular central Gaussian log-likelihood",
      "topics": [
        "acg_loglik"
      ]
    },
    {
      "page": "bai_saranadasa_two_sample_test",
      "title": "Original Bai-Saranadasa two-sample mean test",
      "topics": [
        "bai_saranadasa_two_sample_test"
      ]
    },
    {
      "page": "basic_shape",
      "title": "BASIC bias-adjusted spatial-sign shape estimator",
      "topics": [
        "basic_shape"
      ]
    },
    {
      "page": "basics_shape",
      "title": "BASICS shrinkage plus bias-adjusted shape estimator",
      "topics": [
        "basics_shape"
      ]
    },
    {
      "page": "bickel_levina_covariance_threshold",
      "title": "Bickel-Levina hard-thresholded covariance estimator",
      "topics": [
        "bickel_levina_covariance_threshold"
      ]
    },
    {
      "page": "book_gaussian_alpha_cauchy_test",
      "title": "Book Gaussian alpha Cauchy benchmark",
      "topics": [
        "book_gaussian_alpha_cauchy_test"
      ]
    },
    {
      "page": "cai_liu_adaptive_covariance_threshold",
      "title": "Cai-Liu adaptive covariance thresholding",
      "topics": [
        "cai_liu_adaptive_covariance_threshold"
      ]
    },
    {
      "page": "cai_liu_xia_two_sample_test",
      "title": "Cai-Liu-Xia precision-adjusted two-sample maximum test",
      "topics": [
        "cai_liu_xia_two_sample_test"
      ]
    },
    {
      "page": "cca_bartlett_test",
      "title": "Bartlett likelihood-ratio approximation for canonical correlations",
      "topics": [
        "cca_bartlett_test"
      ]
    },
    {
      "page": "chen_qin_two_sample_test",
      "title": "Chen-Qin two-sample high-dimensional mean test",
      "topics": [
        "chen_qin_two_sample_test"
      ]
    },
    {
      "page": "chen_song_feng_rank_white_noise_test",
      "title": "Chen-Song-Feng rank-based max white-noise test",
      "topics": [
        "chen_song_feng_rank_white_noise_test"
      ]
    },
    {
      "page": "chen_zhang_zhong_covariance_test",
      "title": "Chen-Zhang-Zhong high-dimensional covariance test",
      "topics": [
        "chen_zhang_zhong_covariance_test"
      ]
    },
    {
      "page": "cheng_sscm_equality_test",
      "title": "Cheng-Liu-Peng-Zhang-Zheng two-sample SSCM test",
      "topics": [
        "cheng_sscm_equality_test"
      ]
    },
    {
      "page": "chime_clustering",
      "title": "CHIME clustering for a two-component Gaussian mixture",
      "topics": [
        "chime_clustering"
      ]
    },
    {
      "page": "classical_cca",
      "title": "Classical canonical correlation analysis",
      "topics": [
        "classical_cca"
      ]
    },
    {
      "page": "classical_cusum_test",
      "title": "Classical CUSUM change-point test",
      "topics": [
        "classical_cusum_test"
      ]
    },
    {
      "page": "classical_lda_classifier",
      "title": "Classical plug-in linear discriminant classifier",
      "topics": [
        "classical_lda_classifier"
      ]
    },
    {
      "page": "classical_pca",
      "title": "Classical principal component analysis with explicit covariance convention",
      "topics": [
        "classical_pca"
      ]
    },
    {
      "page": "classical_qda_classifier",
      "title": "Classical plug-in quadratic discriminant classifier",
      "topics": [
        "classical_qda_classifier"
      ]
    },
    {
      "page": "classical_spatial_tests",
      "title": "Classical spatial sign and rank location tests",
      "topics": [
        "classical_spatial_tests",
        "spatial_rank_test",
        "spatial_signed_rank_test",
        "spatial_sign_test"
      ]
    },
    {
      "page": "clime_precision",
      "title": "Gaussian CLIME sparse precision estimator",
      "topics": [
        "clime_precision"
      ]
    },
    {
      "page": "composite_t2_two_sample_test",
      "title": "Feng-Zou-Wang-Zhu Composite T-squared two-sample test",
      "topics": [
        "composite_t2_two_sample_test"
      ]
    },
    {
      "page": "conditional_alpha_sieve_design",
      "title": "Construct a conditional-alpha sieve design from a supplied basis",
      "topics": [
        "conditional_alpha_sieve_design"
      ]
    },
    {
      "page": "conditional_alpha_sieve_fit",
      "title": "Fit the restricted conditional-alpha sieve regression",
      "topics": [
        "conditional_alpha_sieve_fit"
      ]
    },
    {
      "page": "conditional_factor_wald_test",
      "title": "Fixed-dimensional conditional-factor Wald benchmark",
      "topics": [
        "conditional_factor_wald_test"
      ]
    },
    {
      "page": "dsda_classifier",
      "title": "Direct sparse discriminant analysis",
      "topics": [
        "dsda_classifier"
      ]
    },
    {
      "page": "ec2_covariance",
      "title": "EC2 sparse covariance estimation with an eigenvalue constraint",
      "topics": [
        "ec2_covariance"
      ]
    },
    {
      "page": "elliptical_factor_number",
      "title": "Select the number of spikes in an elliptical factor model",
      "topics": [
        "elliptical_factor_number"
      ]
    },
    {
      "page": "elliptical_factor_precision",
      "title": "Sparse precision estimation for an elliptical factor fit",
      "topics": [
        "elliptical_factor_precision"
      ]
    },
    {
      "page": "elliptical_oracle_classifier",
      "title": "Exact oracle classifier for two elliptical populations",
      "topics": [
        "elliptical_oracle_classifier"
      ]
    },
    {
      "page": "elliptical_regularized_hotelling_cauchy_test",
      "title": "Elliptical regularized Hotelling test with Cauchy aggregation",
      "topics": [
        "elliptical_regularized_hotelling_cauchy_test"
      ]
    },
    {
      "page": "elliptical_regularized_hotelling_test",
      "title": "Elliptical regularized Hotelling fixed-ridge test",
      "topics": [
        "elliptical_regularized_hotelling_test"
      ]
    },
    {
      "page": "erht_change_point_test",
      "title": "Elliptical regularized Hotelling change-point scan",
      "topics": [
        "erht_change_point_test"
      ]
    },
    {
      "page": "erht_wbs",
      "title": "Wild binary segmentation with the ERHT local score",
      "topics": [
        "erht_wbs"
      ]
    },
    {
      "page": "fair_classifier",
      "title": "Features annealed independence rule (FAIR)",
      "topics": [
        "fair_classifier"
      ]
    },
    {
      "page": "fantope_pca",
      "title": "Fantope projection and selection sparse PCA",
      "topics": [
        "fantope_pca"
      ]
    },
    {
      "page": "feng_jiang_liu_xiong_panel_independence_test",
      "title": "Feng-Jiang-Liu-Xiong max-sum panel-independence test",
      "topics": [
        "feng_jiang_liu_xiong_panel_independence_test"
      ]
    },
    {
      "page": "feng_lan_liu_ma_alpha_max_test",
      "title": "Feng-Lan-Liu-Ma high-dimensional maximum alpha test",
      "topics": [
        "feng_lan_liu_ma_alpha_max_test"
      ]
    },
    {
      "page": "feng_liu_ma_white_noise_test",
      "title": "Feng-Liu-Ma high-dimensional white-noise test",
      "topics": [
        "feng_liu_ma_white_noise_test"
      ]
    },
    {
      "page": "feng_liu_rank_sphericity_test",
      "title": "Feng-Liu spatial-rank sphericity tests",
      "topics": [
        "feng_liu_rank_sphericity_test"
      ]
    },
    {
      "page": "feng_spatial_rank_proportionality_test",
      "title": "Feng-Zhang-Liu spatial-rank proportionality test",
      "topics": [
        "feng_spatial_rank_proportionality_test"
      ]
    },
    {
      "page": "feng_sun_one_sample_test",
      "title": "Feng-Sun scalar-invariant one-sample spatial-sign test",
      "topics": [
        "feng_sun_one_sample_test"
      ]
    },
    {
      "page": "feng_wang_pdq_two_sample_test",
      "title": "Feng-Wang pairwise-difference-quantile spatial-sign test",
      "topics": [
        "feng_wang_pdq_two_sample_test"
      ]
    },
    {
      "page": "feng_zhang_liu_spatial_rank_test",
      "title": "Feng-Zhang-Liu high-dimensional two-sample spatial-rank test",
      "topics": [
        "feng_zhang_liu_spatial_rank_test"
      ]
    },
    {
      "page": "feng_zou_wang_two_sample_sign_test",
      "title": "Feng-Zou-Wang two-sample multivariate-sign test",
      "topics": [
        "feng_zou_wang_two_sample_sign_test"
      ]
    },
    {
      "page": "feng_zou_wang_zhu_two_sample_test",
      "title": "Feng-Zou-Wang-Zhu scale-invariant Behrens-Fisher test",
      "topics": [
        "feng_zou_wang_zhu_two_sample_test"
      ]
    },
    {
      "page": "fisher_sun_gallagher_sphericity_test",
      "title": "Fisher-Sun-Gallagher fourth-to-second trace sphericity test",
      "topics": [
        "fisher_sun_gallagher_sphericity_test"
      ]
    },
    {
      "page": "gaussian_alpha_combination_test",
      "title": "Feng-Lan-Liu-Ma adaptive Gaussian alpha test",
      "topics": [
        "gaussian_alpha_combination_test"
      ]
    },
    {
      "page": "gaussian_covariance_lrt",
      "title": "Classical Gaussian likelihood-ratio test for a covariance matrix",
      "topics": [
        "gaussian_covariance_lrt"
      ]
    },
    {
      "page": "gaussian_graphical_lasso",
      "title": "Gaussian graphical lasso with an off-diagonal penalty",
      "topics": [
        "gaussian_graphical_lasso"
      ]
    },
    {
      "page": "gaussian_lda_oracle",
      "title": "Oracle Gaussian linear discriminant classifier",
      "topics": [
        "gaussian_lda_oracle"
      ]
    },
    {
      "page": "gaussian_mixture_em",
      "title": "Full-covariance Gaussian-mixture EM",
      "topics": [
        "gaussian_mixture_em"
      ]
    },
    {
      "page": "gaussian_qda_oracle",
      "title": "Oracle Gaussian quadratic discriminant classifier",
      "topics": [
        "gaussian_qda_oracle"
      ]
    },
    {
      "page": "gaussian_wilks_independence_test",
      "title": "Gaussian Wilks block-independence test",
      "topics": [
        "gaussian_wilks_independence_test"
      ]
    },
    {
      "page": "generalized_sign_pca",
      "title": "Generalized spatial-sign principal component analysis",
      "topics": [
        "generalized_sign_pca"
      ]
    },
    {
      "page": "generic_weighted_hr_location",
      "title": "Generic weighted Hettmansperger-Randles location estimator",
      "topics": [
        "generic_weighted_hr_location"
      ]
    },
    {
      "page": "gqda_classifier",
      "title": "Generalized quadratic discriminant analysis for elliptical populations",
      "topics": [
        "gqda_classifier"
      ]
    },
    {
      "page": "grs_alpha_test",
      "title": "Gibbons-Ross-Shanken exact alpha test",
      "topics": [
        "grs_alpha_test"
      ]
    },
    {
      "page": "hallin_paindaveine_shape_test",
      "title": "Hallin-Paindaveine signed-rank test for elliptical shape",
      "topics": [
        "hallin_paindaveine_shape_test"
      ]
    },
    {
      "page": "hd_classifier_fit",
      "title": "Construct a classifier from a scoring function",
      "topics": [
        "hd_classifier_fit"
      ]
    },
    {
      "page": "high_dimensional_hr",
      "title": "High-dimensional Hettmansperger-Randles estimation",
      "topics": [
        "high_dimensional_hr"
      ]
    },
    {
      "page": "hotelling_tests",
      "title": "Classical Hotelling location tests",
      "topics": [
        "hotelling_one_sample_test",
        "hotelling_tests",
        "hotelling_two_sample_test"
      ]
    },
    {
      "page": "hr_estimator",
      "title": "Hettmansperger-Randles affine-equivariant location and shape",
      "topics": [
        "hr_estimator"
      ]
    },
    {
      "page": "hr_gqda",
      "title": "High-dimensional HR generalized quadratic discriminant analysis",
      "topics": [
        "hr_gqda",
        "hr_qda"
      ]
    },
    {
      "page": "if_pca",
      "title": "Influential features PCA clustering",
      "topics": [
        "if_pca"
      ]
    },
    {
      "page": "independence_classifier",
      "title": "Diagonal-covariance independence classifier",
      "topics": [
        "independence_classifier"
      ]
    },
    {
      "page": "inst_one_sample_test",
      "title": "Feng-Liu-Ma one-sample inverse norm sign test",
      "topics": [
        "inst_one_sample_test"
      ]
    },
    {
      "page": "jiang_da_qda",
      "title": "Jiang-Wang-Leng direct sparse QDA",
      "topics": [
        "jiang_da_qda"
      ]
    },
    {
      "page": "john_sphericity_test",
      "title": "John's classical trace test of Gaussian sphericity",
      "topics": [
        "john_sphericity_test"
      ]
    },
    {
      "page": "k_spatial_median",
      "title": "K-spatial-median clustering",
      "topics": [
        "k_spatial_median"
      ]
    },
    {
      "page": "kendall_factor_number",
      "title": "Robust factor-number selection from multivariate Kendall eigenvalues",
      "topics": [
        "kendall_factor_number"
      ]
    },
    {
      "page": "kendall_pca",
      "title": "Multivariate-Kendall principal component analysis",
      "topics": [
        "kendall_pca"
      ]
    },
    {
      "page": "li_chen_covariance_test",
      "title": "Li-Chen two-sample high-dimensional covariance equality test",
      "topics": [
        "li_chen_covariance_test"
      ]
    },
    {
      "page": "li_shao_sparse_qda",
      "title": "Li-Shao thresholded sparse QDA",
      "topics": [
        "li_shao_sparse_qda"
      ]
    },
    {
      "page": "li_wang_zou_two_sample_sign_test",
      "title": "Li-Wang-Zou simpler spatial-sign-based two-sample test",
      "topics": [
        "li_wang_zou_two_sample_sign_test"
      ]
    },
    {
      "page": "linear_pool_covariance",
      "title": "Linear or convex pooling of covariance matrices",
      "topics": [
        "linear_pool_covariance"
      ]
    },
    {
      "page": "liu_feng_ma_spatial_sign_alpha_test",
      "title": "Liu-Feng-Ma robust spatial-sign sum alpha test",
      "topics": [
        "liu_feng_ma_spatial_sign_alpha_test"
      ]
    },
    {
      "page": "lloyd_kmeans",
      "title": "Lloyd's deterministic K-means algorithm",
      "topics": [
        "lloyd_kmeans"
      ]
    },
    {
      "page": "lpd_classifier",
      "title": "Linear programming discriminant classifier",
      "topics": [
        "lpd_classifier"
      ]
    },
    {
      "page": "ma_feng_wang_bao_conditional_alpha_test",
      "title": "Ma-Feng-Wang-Bao conditional maximum and adaptive alpha test",
      "topics": [
        "ma_feng_wang_bao_conditional_alpha_test"
      ]
    },
    {
      "page": "ma_lan_su_tsai_conditional_alpha_sum_test",
      "title": "Ma-Lan-Su-Tsai conditional high-dimensional alpha sum test",
      "topics": [
        "ma_lan_su_tsai_conditional_alpha_sum_test"
      ]
    },
    {
      "page": "mauchly_sphericity_test",
      "title": "Mauchly-Box likelihood-ratio test of Gaussian sphericity",
      "topics": [
        "mauchly_sphericity_test"
      ]
    },
    {
      "page": "nagao_identity_test",
      "title": "Nagao's classical Gaussian identity-covariance test",
      "topics": [
        "nagao_identity_test"
      ]
    },
    {
      "page": "normalize_shape",
      "title": "Normalize a shape matrix",
      "topics": [
        "normalize_shape"
      ]
    },
    {
      "page": "ollila_raninen_shrinkage_covariance",
      "title": "Ollila-Raninen elliptical shrinkage covariance estimator",
      "topics": [
        "ollila_raninen_shrinkage_covariance"
      ]
    },
    {
      "page": "oracle_weighted_sign_sum_test",
      "title": "Oracle generic weighted-sign sum statistic",
      "topics": [
        "oracle_weighted_sign_sum_test"
      ]
    },
    {
      "page": "park_ayyala_one_sample_test",
      "title": "Park-Ayyala one-sample high-dimensional mean test",
      "topics": [
        "park_ayyala_one_sample_test"
      ]
    },
    {
      "page": "pesaran_cd_test",
      "title": "Pesaran CD test for cross-sectional independence",
      "topics": [
        "pesaran_cd_test"
      ]
    },
    {
      "page": "pesaran_yamagata_alpha_test",
      "title": "Pesaran-Yamagata large-N sum alpha test",
      "topics": [
        "pesaran_yamagata_alpha_test"
      ]
    },
    {
      "page": "pmd_sparse_cca",
      "title": "Penalized-matrix-decomposition sparse CCA",
      "topics": [
        "pmd_sparse_cca"
      ]
    },
    {
      "page": "pmd_sparse_pca",
      "title": "Penalized-matrix-decomposition sparse PCA",
      "topics": [
        "pmd_sparse_pca"
      ]
    },
    {
      "page": "poet_covariance",
      "title": "POET covariance estimator with a supplied factor count",
      "topics": [
        "poet_covariance"
      ]
    },
    {
      "page": "poet_tme",
      "title": "One-step Tyler POET estimator for an elliptical factor model",
      "topics": [
        "poet_tme"
      ]
    },
    {
      "page": "predict.hd_classifier_fit",
      "title": "Predict from a Chapter 5 classifier",
      "topics": [
        "predict.hd_classifier_fit"
      ]
    },
    {
      "page": "predict.semc_fit",
      "title": "Predict from a semiparametric elliptical mixture fit",
      "topics": [
        "predict.semc_fit"
      ]
    },
    {
      "page": "regularized_spatial_sign_covariance",
      "title": "Regularized spatial-sign covariance (RSSCM)",
      "topics": [
        "regularized_spatial_sign_covariance"
      ]
    },
    {
      "page": "relliptical",
      "title": "Simulate an elliptically symmetric sample",
      "topics": [
        "relliptical"
      ]
    },
    {
      "page": "robust_factor_subspace",
      "title": "Robust principal subspace for an elliptical factor model",
      "topics": [
        "robust_factor_subspace"
      ]
    },
    {
      "page": "robust_gqda",
      "title": "Generalized QDA from certified robust class fits",
      "topics": [
        "robust_gqda"
      ]
    },
    {
      "page": "rothman_levina_zhu_covariance_threshold",
      "title": "Rothman-Levina-Zhu generalized covariance thresholding",
      "topics": [
        "rothman_levina_zhu_covariance_threshold"
      ]
    },
    {
      "page": "rspherical",
      "title": "Simulate a spherically symmetric sample",
      "topics": [
        "rspherical"
      ]
    },
    {
      "page": "rts_factor",
      "title": "Robust two-step factor estimator based on multivariate Kendall's tau",
      "topics": [
        "rts_factor"
      ]
    },
    {
      "page": "scaled_spatial_median",
      "title": "Scaled spatial median with diagonal HR standardisation",
      "topics": [
        "scaled_spatial_median"
      ]
    },
    {
      "page": "sdar_qda",
      "title": "Sparse discriminant analysis with quadratic interactions",
      "topics": [
        "sdar_qda"
      ]
    },
    {
      "page": "semc_fit",
      "title": "Semiparametric elliptical mixture clustering",
      "topics": [
        "semc_fit"
      ]
    },
    {
      "page": "semc_select_k_gap",
      "title": "Select the SEMC cluster count by Gap-LSE",
      "topics": [
        "semc_select_k_gap"
      ]
    },
    {
      "page": "shao_threshold_lda",
      "title": "Shao-Wang-Deng-Wang thresholded sparse LDA",
      "topics": [
        "shao_threshold_lda"
      ]
    },
    {
      "page": "sign_whitened_sparse_cca",
      "title": "Book sign-whitened sparse CCA variant",
      "topics": [
        "sign_whitened_sparse_cca"
      ]
    },
    {
      "page": "sm_sscm",
      "title": "Spatial-median clustering with a common SSCM metric",
      "topics": [
        "sm_sscm"
      ]
    },
    {
      "page": "sparse_k_spatial_median",
      "title": "Sparse K-spatial-median clustering",
      "topics": [
        "sparse_k_spatial_median"
      ]
    },
    {
      "page": "sparse_kmeans",
      "title": "Sparse K-means with ordered-pair BCSS weights",
      "topics": [
        "sparse_kmeans"
      ]
    },
    {
      "page": "sparse_kmeans_select_s",
      "title": "Select the sparse K-means L1 bound by permutation Gap calibration",
      "topics": [
        "sparse_kmeans_select_s"
      ]
    },
    {
      "page": "sparse_kmedian",
      "title": "Coordinatewise sparse K-median clustering",
      "topics": [
        "sparse_kmedian"
      ]
    },
    {
      "page": "sparse_plugin_lda",
      "title": "Sparse matrix plug-in LDA classifier",
      "topics": [
        "sparse_plugin_lda"
      ]
    },
    {
      "page": "sparse_plugin_qda",
      "title": "Certified sparse plug-in QDA",
      "topics": [
        "sparse_plugin_qda"
      ]
    },
    {
      "page": "sparse_sm_select_k",
      "title": "Select K for Sparse-SM by the BWDM rule",
      "topics": [
        "sparse_sm_select_k"
      ]
    },
    {
      "page": "sparse_sm_select_tau",
      "title": "Select the Sparse-SM threshold by the permutation Gap criterion",
      "topics": [
        "sparse_sm_select_tau"
      ]
    },
    {
      "page": "sparse_spatial_sign_pca",
      "title": "Sparse spatial-sign principal component analysis",
      "topics": [
        "sparse_spatial_sign_pca"
      ]
    },
    {
      "page": "spatial_kendall",
      "title": "Multivariate spatial Kendall matrix",
      "topics": [
        "spatial_kendall"
      ]
    },
    {
      "page": "spatial_median",
      "title": "Spatial median",
      "topics": [
        "spatial_median"
      ]
    },
    {
      "page": "spatial_rank",
      "title": "Empirical spatial ranks",
      "topics": [
        "spatial_rank"
      ]
    },
    {
      "page": "spatial_rank_covariance",
      "title": "Spatial rank covariance matrix",
      "topics": [
        "spatial_rank_covariance"
      ]
    },
    {
      "page": "spatial_sign",
      "title": "Spatial signs",
      "topics": [
        "spatial_sign"
      ]
    },
    {
      "page": "spatial_sign_change_point_test",
      "title": "Spatial-sign max-Linf, max-L2, and adaptive change-point test",
      "topics": [
        "spatial_sign_change_point_test"
      ]
    },
    {
      "page": "spatial_sign_max_test",
      "title": "Spatial-sign max test for a high-dimensional location",
      "topics": [
        "spatial_sign_max_test"
      ]
    },
    {
      "page": "spatial_sign_maxsum_test",
      "title": "Spatial-sign max-sum test for a high-dimensional location",
      "topics": [
        "spatial_sign_maxsum_test"
      ]
    },
    {
      "page": "spatial_sign_pca",
      "title": "Spatial-sign principal component analysis",
      "topics": [
        "spatial_sign_pca"
      ]
    },
    {
      "page": "spatial_sign_poet",
      "title": "Spatial-sign POET estimator for an elliptical factor model",
      "topics": [
        "spatial_sign_poet"
      ]
    },
    {
      "page": "spatial_sign_precision",
      "title": "Robust spatial-sign SCLIME and SGLASSO precision estimation",
      "topics": [
        "spatial_sign_precision"
      ]
    },
    {
      "page": "spatial_sign_precision_lda",
      "title": "Spatial-sign precision plug-in LDA",
      "topics": [
        "spatial_sign_precision_lda"
      ]
    },
    {
      "page": "spatial_sign_sphericity_test",
      "title": "Spatial-sign sphericity test",
      "topics": [
        "spatial_sign_sphericity_test"
      ]
    },
    {
      "page": "srivastava_du_one_sample_test",
      "title": "Srivastava-Du one-sample high-dimensional mean test",
      "topics": [
        "srivastava_du_one_sample_test"
      ]
    },
    {
      "page": "srivastava_katayama_kano_two_sample_test",
      "title": "Srivastava-Katayama-Kano two-sample mean test",
      "topics": [
        "srivastava_katayama_kano_two_sample_test"
      ]
    },
    {
      "page": "sscca",
      "title": "Primary spatial-sign sparse canonical correlation analysis",
      "topics": [
        "sscca"
      ]
    },
    {
      "page": "sscm",
      "title": "Spatial sign covariance matrix",
      "topics": [
        "sscm"
      ]
    },
    {
      "page": "sslda",
      "title": "Spatial-sign direct sparse linear discriminant analysis",
      "topics": [
        "sslda"
      ]
    },
    {
      "page": "ssqda",
      "title": "Spatial-sign sparse quadratic discriminant analysis",
      "topics": [
        "ssqda"
      ]
    },
    {
      "page": "tensor_spatial_sign_precision",
      "title": "Sparse tensor-elliptical precision matrices from tensor spatial signs",
      "topics": [
        "tensor_spatial_sign_precision"
      ]
    },
    {
      "page": "threshold_spatial_sign_precision",
      "title": "Threshold a spatial-sign precision estimate",
      "topics": [
        "threshold_spatial_sign_precision"
      ]
    },
    {
      "page": "threshold_tensor_spatial_sign_precision",
      "title": "Threshold fitted tensor spatial-sign precision matrices",
      "topics": [
        "threshold_tensor_spatial_sign_precision"
      ]
    },
    {
      "page": "tinst_two_sample_test",
      "title": "Huang-Liu-Zhou-Feng two-sample inverse norm sign test",
      "topics": [
        "tinst_two_sample_test"
      ]
    },
    {
      "page": "truncated_power_pca",
      "title": "Truncated-power sparse principal components",
      "topics": [
        "truncated_power_pca"
      ]
    },
    {
      "page": "tyler_shape",
      "title": "Tyler's shape estimator",
      "topics": [
        "tyler_shape"
      ]
    },
    {
      "page": "wang_feng_dms_test",
      "title": "Wang-Feng double-max-sum change-point test",
      "topics": [
        "wang_feng_dms_test"
      ]
    },
    {
      "page": "wang_liu_feng_ma_serial_panel_test",
      "title": "Wang-Liu-Feng-Ma serial-panel Fisher independence test",
      "topics": [
        "wang_liu_feng_ma_serial_panel_test"
      ]
    },
    {
      "page": "wang_liu_feng_vector_independence_test",
      "title": "Wang-Liu-Feng rank max-sum test for vector independence",
      "topics": [
        "wang_liu_feng_vector_independence_test"
      ]
    },
    {
      "page": "wang_liu_feng_vector_u_independence_test",
      "title": "Wang-Liu-Feng degenerate rank-U vector-independence test",
      "topics": [
        "wang_liu_feng_vector_u_independence_test"
      ]
    },
    {
      "page": "wang_peng_li_one_sample_test",
      "title": "Wang-Peng-Li one-sample high-dimensional spatial-sign test",
      "topics": [
        "wang_peng_li_one_sample_test"
      ]
    },
    {
      "page": "wang_xu_approx_randomization_test",
      "title": "Wang-Xu approximate randomization test",
      "topics": [
        "wang_xu_approx_randomization_test"
      ]
    },
    {
      "page": "wang_yao_corrected_john_test",
      "title": "Wang-Yao corrected John's test of sphericity",
      "topics": [
        "wang_yao_corrected_john_test"
      ]
    },
    {
      "page": "wang_yao_corrected_lrt",
      "title": "Wang-Yao corrected likelihood-ratio test of sphericity",
      "topics": [
        "wang_yao_corrected_lrt"
      ]
    },
    {
      "page": "wang_zhao_feng_wang_mutual_fund_fdr",
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