Pages that link to "Item:Q4602114"

The following pages link to Two-sample tests for high-dimension, strongly spiked eigenvalue models (Q4602114):

Displaying 47 items.

• On two-sample mean tests under spiked covariances (Q1661347) (← links)
• On simultaneous confidence interval estimation for the difference of paired mean vectors in high-dimensional settings (Q1795576) (← links)
• Distance-based classifier by data transformation for high-dimension, strongly spiked eigenvalue models (Q2000734) (← links)
• Bias-corrected support vector machine with Gaussian kernel in high-dimension, low-sample-size settings (Q2023463) (← links)
• Consistent variable selection criteria in multivariate linear regression even when dimension exceeds sample size (Q2041755) (← links)
• Hypothesis tests for high-dimensional covariance structures (Q2042528) (← links)
• Clustering by principal component analysis with Gaussian kernel in high-dimension, low-sample-size settings (Q2048123) (← links)
• Linear hypothesis testing in high-dimensional heteroscedastic one-way MANOVA: a normal reference \(L^2\)-norm based test (Q2057832) (← links)
• Geometric classifiers for high-dimensional noisy data (Q2062792) (← links)
• Recent developments in high-dimensional inference for multivariate data: parametric, semiparametric and nonparametric approaches (Q2062798) (← links)
• Asymptotic properties of distance-weighted discrimination and its bias correction for high-dimension, low-sample-size data (Q2068931) (← links)
• Consistency of the objective general index in high-dimensional settings (Q2078579) (← links)
• Contrastive latent variable modeling with application to case-control sequencing experiments (Q2170381) (← links)
• Two-way MANOVA with unequal cell sizes and unequal cell covariance matrices in high-dimensional settings (Q2196118) (← links)
• Limit theorem associated with Wishart matrices with application to hypothesis testing for common principal components (Q2237828) (← links)
• On asymptotic normality of cross data matrix-based PCA in high dimension low sample size (Q2293385) (← links)
• Equality tests of high-dimensional covariance matrices under the strongly spiked eigenvalue model (Q2317309) (← links)
• Location-invariant tests of homogeneity of large-dimensional covariance matrices (Q2321809) (← links)
• Inference on high-dimensional mean vectors under the strongly spiked eigenvalue model (Q2329874) (← links)
• A Behrens-Fisher problem for general factor models in high dimensions (Q2692937) (← links)
• A High-Dimensional Two-Sample Test for Non-Gaussian Data under a Strongly Spiked Eigenvalue Model (Q4578226) (← links)
• A test of sphericity for high-dimensional data and its application for detection of divergently spiked noise (Q4632469) (← links)
• A survey of high dimension low sample size asymptotics (Q4639812) (← links)
• (Q5004041) (← links)
• High-dimensional MANOVA under weak conditions (Q5004986) (← links)
• (Q5011468) (← links)
• A classifier under the strongly spiked eigenvalue model in high-dimension, low-sample-size context (Q5077372) (← links)
• High dimensional asymptotics for the naive Hotelling <i>T</i>² statistic in pattern recognition (Q5077925) (← links)
• Simultaneous testing of the mean vector and covariance matrix among <i>k</i> populations for high-dimensional data (Q5079065) (← links)
• High-dimensional rank-based inference (Q5114476) (← links)
• A Simple Two-Sample Test in High Dimensions Based on <i>L</i>²-Norm (Q5130640) (← links)
• Discussion of “A Scale-Free Approach for False Discovery Rate Control in Generalized Linear Models” by Dai, Lin, Xing, and Liu (Q6077544) (← links)
• Linear Hypothesis Testing in Linear Models With High-Dimensional Responses (Q6110696) (← links)
• High-dimensional hypothesis testing for allometric extension model (Q6113076) (← links)
• Polynomial whitening for high-dimensional data (Q6178887) (← links)
• A high‐dimensional inverse norm sign test for two‐sample location problems (Q6180916) (← links)
• A Pairwise Hotelling Method for Testing High-Dimensional Mean Vectors (Q6185128) (← links)
• Joint test for homogeneity of high-dimensional means and covariance matrices using maximum-type statistics (Q6552995) (← links)
• Statistical inference under the strongly spiked eigenvalue model (Q6601514) (← links)
• Two-sample test for high-dimensional covariance matrices: a normal-reference approach (Q6615372) (← links)
• Cross projection test for mean vectors via multiple random splits in high dimensions (Q6615377) (← links)
• Some clustering-based change-point detection methods applicable to high dimension, low sample size data (Q6616205) (← links)
• An adaptive weighted component test for high-dimensional means (Q6621345) (← links)
• Testing General Linear Hypotheses Under a High-Dimensional Multivariate Regression Model with Spiked Noise Covariance (Q6651383) (← links)
• Equality tests of covariance matrices under a low-dimensional factor structure (Q6667486) (← links)
• Test for high-dimensional outliers with principal component analysis (Q6670084) (← links)
• Power boosting: fusion of multiple test statistics via resampling (Q6671918) (← links)