| On feature selection, curse-of-dimensionality and error probability in discriminant analysis T Pavlenko Journal of statistical planning and inference 115 (2), 565-584, 2003 | 65 | 2003 |
| Testing linear hypotheses of mean vectors for high-dimension data with unequal covariance matrices T Nishiyama, M Hyodo, T Seo, T Pavlenko Journal of Statistical Planning and Inference 143 (11), 1898-1911, 2013 | 39 | 2013 |
| Credit risk modeling using Bayesian networks T Pavlenko, O Chernyak International Journal of Intelligent Systems 25 (4), 326-344, 2010 | 38 | 2010 |
| Apoptosis, proliferation, and sex steroid receptors in postmenopausal endometrium before and during HRT M Dahmoun, IS Ödmark, B Risberg, MG Karlsson, T Pavlenko, ... Maturitas 49 (2), 114-123, 2004 | 30 | 2004 |
| Lung aeration during sleep J Appelberg, T Pavlenko, H Bergman, HU Rothen, G Hedenstierna Chest 131 (1), 122-129, 2007 | 29 | 2007 |
| Effect of dimensionality on discrimination T Pavlenko, D Von Rosen Statistics 35 (3), 191-213, 2001 | 28 | 2001 |
| Covariance structure approximation via gLasso in high-dimensional supervised classification T Pavlenko, A Björkström, A Tillander Journal of Applied Statistics 39 (8), 1643-1666, 2012 | 26 | 2012 |
| Testing block‐diagonal covariance structure for high‐dimensional data M Hyodo, N Shutoh, T Nishiyama, T Pavlenko Statistica Neerlandica 69 (4), 460-482, 2015 | 21 | 2015 |
| Goodness-of-fit tests based on sup-functionals of weighted empirical processes N Stepanova, T Pavlenko Theory of Probability & Its Applications 63 (2), 292-317, 2018 | 16 | 2018 |
| Asymptotic properties of the misclassification rates for Euclidean distance discriminant rule in high-dimensional data H Watanabe, M Hyodo, T Seo, T Pavlenko Journal of Multivariate Analysis 140, 234-244, 2015 | 13 | 2015 |
| Modified Jarque-Bera type tests for multivariate normality in a high-dimensional framework K Koizumi, M Hyodo, T Pavlenko Journal of Statistical Theory and Practice 8, 382-399, 2014 | 10 | 2014 |
| Sequential sampling of junction trees for decomposable graphs J Olsson, T Pavlenko, FL Rios Statistics and computing 32 (5), 80, 2022 | 7* | 2022 |
| Bayesian learning of weakly structural Markov graph laws using sequential Monte Carlo methods J Olsson, T Pavlenko, FL Rios | 6 | 2019 |
| Measures of multivariate skewness and kurtosis in high-dimensional framework K Koizumi, T Sumikawa, T Pavlenko SUT journal of Mathematics 50 (2), 483-511, 2014 | 6 | 2014 |
| Bayesian block-diagonal predictive classifier for Gaussian data J Corander, T Koski, T Pavlenko, A Tillander Synergies of Soft Computing and Statistics for Intelligent Data Analysis …, 2013 | 6 | 2013 |
| Clinical course of steroid sensitive nephrotic syndrome in children: outcome and outlook S Fomina, T Pavlenko, E Englund, I Bagdasarova The Open Pediatric Medicine Journal 5 (1), 2011 | 6 | 2011 |
| Lung aeration during sleep in patients with obstructive sleep apnoea J Appelberg, C Janson, E Lindberg, T Pavlenko, G Hedenstierna Clinical Physiology and Functional Imaging 30 (4), 301-307, 2010 | 6 | 2010 |
| On error bounds for high-dimensional asymptotic distribution of L2-type test statistic for equality of means M Hyodo, T Nishiyama, T Pavlenko Statistics & Probability Letters 157, 108637, 2020 | 5 | 2020 |
| Multiple comparison procedures for high-dimensional data and their robustness under non-normality S Takahashi, M Hyodo, T Nishiyama, T Pavlenko Journal of the Japanese Society of Computational Statistics 26 (1), 71-82, 2013 | 5 | 2013 |
| On the optimal weighting of high-dimensional Bayesian networks T Pavlenko, D von Rosen Centre of Biostochastics, Swedish University of Agricultural Sciences, 2003 | 5 | 2003 |
Takahiro NishiyamaDepartment of Business Administration, Senshu UniversityVerifierad e-postadress på isc.senshu-u.ac.jp
