The following pages link to (Q4882268):
Displaying 50 items.
- A note on high-dimensional two-sample test (Q894570) (← links)
- Testing of high dimensional mean vectors via approximate factor model (Q897642) (← links)
- Asymptotic properties of the first principal component and equality tests of covariance matrices in high-dimension, low-sample-size context (Q899373) (← links)
- Shrinkage-based diagonal Hotelling's tests for high-dimensional small sample size data (Q900797) (← links)
- Analysis of high-dimensional repeated measures designs: the one sample case (Q961127) (← links)
- High-dimensional classification using features annealed independence rules (Q1000303) (← 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)
- On the \(k\)-sample Behrens-Fisher problem for high-dimensional data (Q1042971) (← links)
- Corrections to LRT on large-dimensional covariance matrix by RMT (Q1043713) (← links)
- Adaptive test for mean vectors of high-dimensional time series data with factor structure (Q1622117) (← links)
- A high-dimensional two-sample test for the mean using random subspaces (Q1623444) (← links)
- Test for high-dimensional regression coefficients using refitted cross-validation variance estimation (Q1650066) (← links)
- Ball divergence: nonparametric two sample test (Q1650071) (← links)
- Self-normalization: taming a wild population in a heavy-tailed world (Q1650693) (← 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)
- Jackknife empirical likelihood test for high-dimensional regression coefficients (Q1660165) (← links)
- On two-sample mean tests under spiked covariances (Q1661347) (← links)
- A test for equality of two distributions via jackknife empirical likelihood and characteristic functions (Q1663149) (← links)
- An adaptive test for the mean vector in large-\(p\)-small-\(n\) problems (Q1663250) (← links)
- Tests for comparison of multiple endpoints with application to omics data (Q1672809) (← links)
- Variance-corrected tests for covariance structures with high-dimensional data (Q1679563) (← links)
- Comparison of a large number of regression curves (Q1679568) (← links)
- Asymptotic normality of quadratic forms with random vectors of increasing dimension (Q1686240) (← links)
- A note on the unbiased estimator of \(\mathbf{\Sigma}^2\) (Q1687204) (← links)
- Distribution-free high-dimensional two-sample tests based on discriminating hyperplanes (Q1694021) (← links)
- Generalized F-test for high dimensional regression coefficients of partially linear models (Q1697682) (← links)
- On LR simultaneous test of high-dimensional mean vector and covariance matrix under non-normality (Q1726809) (← links)
- Empirical likelihood for heteroscedastic partially linear single-index models with growing dimensional data (Q1744028) (← links)
- Testing independence with high-dimensional correlated samples (Q1750290) (← links)
- Projection tests for high-dimensional spiked covariance matrices (Q1755108) (← links)
- Robust two-sample test of high-dimensional mean vectors under dependence (Q1755128) (← links)
- On the dimension effect of regularized linear discriminant analysis (Q1786573) (← links)
- Inference for high-dimensional split-plot-designs: a unified approach for small to large numbers of factor levels (Q1786575) (← links)
- On simultaneous confidence interval estimation for the difference of paired mean vectors in high-dimensional settings (Q1795576) (← links)
- Change-point detection in multinomial data with a large number of categories (Q1800792) (← 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)
- Inference on high-dimensional mean vectors with fewer observations than the dimension (Q1930608) (← 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)
- Robust multivariate nonparametric tests via projection averaging (Q1996775) (← links)
- Distance-based classifier by data transformation for high-dimension, strongly spiked eigenvalue models (Q2000734) (← links)
- Tests for regression coefficients in high dimensional partially linear models (Q2006717) (← links)
- A two-sample test for the equality of univariate marginal distributions for high-dimensional data (Q2008229) (← links)
- Bias-corrected support vector machine with Gaussian kernel in high-dimension, low-sample-size settings (Q2023463) (← links)
- Tests for \(p\)-regression coefficients in linear panel model when \(p\) is divergent (Q2023728) (← links)
- A stationary bootstrap test about two mean vectors comparison with somewhat dense differences and fewer sample size than dimension (Q2032194) (← links)
- A high dimensional nonparametric test for proportional covariance matrices (Q2034477) (← links)
