Pages that link to "Item:Q5633443"

The following pages link to A High Dimensional Two Sample Significance Test (Q5633443):

Displaying 50 items.

• Asymptotic distributions of some test criteria for the mean vector with fewer observations than the dimension (Q391567) (← links)
• Testing linear hypotheses of mean vectors for high-dimension data with unequal covariance matrices (Q394093) (← links)
• A modified two-factor multivariate analysis of variance: asymptotics and small sample approxi\-mations (Q421396) (← links)
• Likelihood ratio tests for covariance matrices of high-dimensional normal distributions (Q433736) (← links)
• Linear hypothesis testing in high-dimensional one-way MANOVA (Q512013) (← links)
• On testing the equality of high dimensional mean vectors with unequal covariance matrices (Q520564) (← links)
• A review of 20 years of naive tests of significance for high-dimensional mean vectors and covariance matrices (Q525878) (← links)
• Data depth trimming counterpart of the classical \(t\) (or \(T^2\)) procedure (Q609674) (← links)
• Contributions to multivariate analysis by Professor Yasunori Fujikoshi (Q855899) (← links)
• Multivariate analysis of variance with fewer observations than the dimension (Q855900) (← links)
• A test for the mean vector with fewer observations than the dimension under non-normality (Q1000578) (← links)
• How to compare small multivariate samples using nonparametric tests (Q1023860) (← links)
• Corrections to LRT on large-dimensional covariance matrix by RMT (Q1043713) (← links)
• A generalized likelihood ratio test for normal mean when \(p\) is greater than \(n\) (Q1659185) (← links)
• A high-dimension two-sample test for the mean using cluster subspaces (Q1659362) (← links)
• An adaptive test for the mean vector in large-\(p\)-small-\(n\) problems (Q1663250) (← links)
• MATS: inference for potentially singular and heteroscedastic MANOVA (Q1742739) (← links)
• Graphical comparisons of multivariate data (Q1821436) (← links)
• Some hypothesis tests for the covariance matrix when the dimension is large compared to the sample size (Q1848966) (← links)
• CLT for linear spectral statistics of large-dimensional sample covariance matrices. (Q1879863) (← links)
• Testing the independence of sets of large-dimensional variables (Q1935713) (← links)
• A test for the mean vector in large dimension and small samples (Q1937204) (← links)
• Limiting behavior of eigenvalues in high-dimensional MANOVA via RMT (Q1991686) (← links)
• Consistent variable selection criteria in multivariate linear regression even when dimension exceeds sample size (Q2041755) (← links)
• High-dimensional linear models: a random matrix perspective (Q2051014) (← links)
• Linear hypothesis testing in high-dimensional heteroscedastic one-way MANOVA: a normal reference \(L^2\)-norm based test (Q2057832) (← links)
• An overview of tests on high-dimensional means (Q2062768) (← links)
• Recent developments in high-dimensional inference for multivariate data: parametric, semiparametric and nonparametric approaches (Q2062798) (← links)
• A new normal reference test for linear hypothesis testing in high-dimensional heteroscedastic one-way MANOVA (Q2076144) (← links)
• Neyman's truncation test for two-sample means under high dimensional setting (Q2077453) (← links)
• Approximate normality in testing an exchangeable covariance structure under large- and high-dimensional settings (Q2079602) (← links)
• Testing high-dimensional mean vector with applications. A normal reference approach (Q2165834) (← links)
• A unified approach to testing mean vectors with large dimensions (Q2176339) (← links)
• A more powerful test of equality of high-dimensional two-sample means (Q2242183) (← links)
• High-dimensional mean estimation via \(\ell_1\) penalized normal likelihood (Q2252887) (← links)
• Tests for covariance matrices in high dimension with less sample size (Q2252902) (← links)
• \(U\)-tests of general linear hypotheses for high-dimensional data under nonnormality and heteroscedasticity (Q2320970) (← links)
• Inference on high-dimensional mean vectors under the strongly spiked eigenvalue model (Q2329874) (← links)
• Testing homogeneity of mean vectors under heteroscedasticity in high-dimension (Q2350049) (← links)
• Mean vector testing for high-dimensional dependent observations (Q2374404) (← links)
• High-dimensional general linear hypothesis testing under heteroscedasticity (Q2407078) (← links)
• A \(U\)-statistic approach for a high-dimensional two-sample mean testing problem under non-normality and Behrens-Fisher setting (Q2434134) (← links)
• Asymptotic power of likelihood ratio tests for high dimensional data (Q2453893) (← links)
• Some high-dimensional tests for a one-way MANOVA (Q2474245) (← links)
• Nonparametric methods in multivariate factorial designs for large number of factor levels (Q2475742) (← links)
• A test for the mean vector with fewer observations than the dimension (Q2476142) (← links)
• Tests for a Multiple-Sample Problem in High Dimensions (Q2815361) (← links)
• On Test Statistics in Profile Analysis with High-dimensional Data (Q2828780) (← links)
• Testing linear hypotheses in high-dimensional regressions (Q2863100) (← links)
• Tests for mean vectors in high dimension (Q2870766) (← links)