Pages that link to "Item:Q5439652"

The following pages link to Multivariate Theory for Analyzing High Dimensional Data (Q5439652):

Displaying 50 items.

• A new test for sphericity of the covariance matrix for high dimensional data (Q149043) (← links)
• Direct shrinkage estimation of large dimensional precision matrix (Q268760) (← links)
• Spectral analysis of the Moore-Penrose inverse of a large dimensional sample covariance matrix (Q276985) (← links)
• Significance analysis of high-dimensional, low-sample size partially labeled data (Q286481) (← links)
• Inference for the mean of large \(p\) small \(n\) data: a finite-sample high-dimensional generalization of Hotelling's theorem (Q358893) (← links)
• Asymptotic distributions of some test criteria for the mean vector with fewer observations than the dimension (Q391567) (← links)
• Correlation tests for high-dimensional data using extended cross-data-matrix methodology (Q391612) (← links)
• Testing linear hypotheses of mean vectors for high-dimension data with unequal covariance matrices (Q394093) (← links)
• High-dimensional sparse MANOVA (Q406532) (← links)
• A model selection criterion for discriminant analysis of high-dimensional data with fewer observations (Q451193) (← links)
• Estimation of the mean vector in a singular multivariate normal distribution (Q495383) (← links)
• On testing the equality of high dimensional mean vectors with unequal covariance matrices (Q520564) (← links)
• Improved multivariate normal mean estimation with unknown covariance when \(p\) is greater than \(n\) (Q741819) (← links)
• Effective PCA for high-dimension, low-sample-size data with noise reduction via geometric representations (Q764487) (← links)
• Multivariate analysis of variance with fewer observations than the dimension (Q855900) (← links)
• Minimum distance classification rules for high dimensional data (Q855920) (← links)
• Singular inverse Wishart distribution and its application to portfolio theory (Q900811) (← links)
• Shrinkage-based regularization tests for high-dimensional data with application to gene set analysis (Q901617) (← links)
• Estimation of the precision matrix of a singular Wishart distribution and its application in high-dimensional data (Q953851) (← links)
• On the Behrens-Fisher problem: a globally convergent algorithm and a finite-sample study of the Wald, LR and LM tests (Q955145) (← links)
• Analysis of high-dimensional repeated measures designs: the one sample case (Q961127) (← links)
• Testing the equality of several covariance matrices with fewer observations than the dimension (Q968483) (← links)
• Statistical eigen-inference from large Wishart matrices (Q1000310) (← links)
• High-dimensional asymptotic expansion of LR statistic for testing intraclass correlation structure and its error bound (Q1041067) (← links)
• Multivariate statistical analysis. A high-dimensional approach (Q1347365) (← links)
• A test for the global minimum variance portfolio for small sample and singular covariance (Q1622106) (← links)
• A high-dimensional two-sample test for the mean using random subspaces (Q1623444) (← 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)
• Hotelling's \(T^2\) in separable Hilbert spaces (Q1661352) (← links)
• Testing and support recovery of multiple high-dimensional covariance matrices with false discovery rate control (Q1694484) (← links)
• Recent advances in shrinkage-based high-dimensional inference (Q2062777) (← links)
• A high-dimensional test for multivariate analysis of variance under a low-dimensional factor structure (Q2100126) (← links)
• Novel multiplier bootstrap tests for high-dimensional data with applications to MANOVA (Q2101406) (← links)
• A rank-based high-dimensional test for equality of mean vectors (Q2143018) (← links)
• Two-way MANOVA with unequal cell sizes and unequal cell covariance matrices in high-dimensional settings (Q2196118) (← links)
• Distribution and correlation-free two-sample test of high-dimensional means (Q2196222) (← links)
• Modified Pillai's trace statistics for two high-dimensional sample covariance matrices (Q2301119) (← links)
• A test for the \(k\) sample Behrens-Fisher problem in high dimensional data (Q2317297) (← 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)
• Test on the linear combinations of mean vectors in high-dimensional data (Q2398084) (← links)
• Likelihood-based tests on moderate-high-dimensional mean vectors with unequal covariance matrices (Q2398414) (← links)
• A combined \(p\)-value test for the mean difference of high-dimensional data (Q2423870) (← links)
• A \(U\)-statistic approach for a high-dimensional two-sample mean testing problem under non-normality and Behrens-Fisher setting (Q2434134) (← links)
• Some high-dimensional tests for a one-way MANOVA (Q2474245) (← links)
• Doubly singular matrix variate beta type I and II and singular inverted matricvariate \(t\) distributions (Q2510705) (← links)
• Tests for a Multiple-Sample Problem in High Dimensions (Q2815361) (← links)
• Tests for mean vectors in high dimension (Q2870766) (← links)
• A Model Selection Criterion for Discriminant Analysis of Several Groups When the Dimension is Larger than the Total Sample Size (Q2920046) (← links)