Academic Papers

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  1. Some inequalities contrasting principal component and factor analyses solutions, Kohei Adachi & Nickolay T. Trendafilov, Japanese Journal of Statistics and Data Science,2(1) 31-47, 2019.05, Papers

  2. Permutimin: Factor Rotation to Simple Structure with Permutation of Variables, Naoto Yamashita & Kohei Adachi, Multivariate Behavioral Research, 2019.04, Papers

  3. Factor Analysis: Latent Variable, Matrix Decomposition, and Constrained Uniqueness Formulations, Kohei Adachi, WIREs Computational Statistcs,in press, 2019.03, Papers

  4. Clustered Common Factor Exploration in Factor Analysis, Kohei Uno, Kohei Adachi, & Nickolay, T. Trendafilov, Psychometrika, 2019.03, Papers

  5. Sparsest factor analysis for clustering variables: A matrix decomposition approach, Kohei Adachi & Nickolay T. Trendafilov, Advances in Data Analysis and Classification,12(3) 559-585, 2018.09, Papers

  6. Some Mathematical Properties of the Matrix Decomposition Solution in Factor Analysis , Kohei Adachi & Nickolay T. Trendafilov, Psychometrika,Vol. 83, Issue 2, pp 407–424, 2018.05, Papers

  7. Sparse Exploratory Factor Analysis, Nickolay T. Trendafilov, Sara Fontanella & Kohei Adachi, Psychometrika,82(3) 778-794, 2017.08, Papers

  8. Sparse principal component analysis subject to prespecified cardinality of loadings, Kohei Adachi & Nickolay T. Trendafilov, Computational Statistics,Vol. 31, No. 4, 1403-1427, 2016.10, Papers

  9. Sparse Tucker2 analysis of three-way data subject to a constrained number of zero elements in a core array, Hiroki Ikemoto & Kohei Adachi, Computational Statistics and Data Analysis,98, 1-18, 2016.05, Papers

  10. Fixed factor analysis with clustered factor score constraint, Kohei Uno, Hironori Satomura, Kohei Adachi, Computational Statistics and Data Analysis,Vol. 94, pp. 265-274, 2016.03, Papers

  11. Sparse versus simple structure loadings, Nickolay T. Trendafilov and Kohei Adachi, Psychometrika,80, 3, 776-790, 2015.09, Papers

  12. A New Algorithm for Generalized Least Squares Factor Analysis with a Majorization Technique, Kohei Adachi, Open Journal of Statistics,Vol. 5, 165-172, 2015.04, Papers

  13. A restrained condition number least squares technique with its applications to avoiding rank deficiency, Kohei Adachi, Journal of the Japanese Society of Computational Statistics,Vol. 26, 39-51 , 2013.12, Papers

  14. Generalized joint Procrustes analysis, Kohei Adachi, Computational Statistics ,Volume 28, Issue 6, pp 2449-2464, 2013.11, Papers

  15. Oblique Rotation in Canonical Correlation Analysis Reformulated as Maximizing the Generalized Coefficient of Determination, Hironori Satomura and Kohei Adachi, Psychometrika,Vol. 78, No. 3, 526-537 , 2013.06, Papers

  16. Factor Analysis with EM Algorithm Never Gives Improper Solutions when Sample Covariance and Initial Parameter Matrices Are Proper, Kohei Adachi, Psychometrika,Vol. 38, Issue 2, 380-394, 2013.03, Papers

  17. Some Contributions to Data-fitting Factor Analysis with Empirical Comprisons to Covariance-fitting Factor Analysis, Kohei Adachi, Journal of Japanese Society of Computational Statistics,Vol. 25, No. 1, pp. 25-38, 2012.12, Papers

  18. Three-Way Tucker2 Component Analysis Solutions of Stimuli x Responses x Individuals Data with Simple Structure and the Fewest Core Differences, Kohei Adachi, Psychometrika,Vol. 76, No. 2, Pp. 285-305, 2011.04, Papers

  19. Constrained Principal Component Analysis of Standardized Data for Biplots with Unit-Length Variable Vectors, Kohei Adachi, Advances in Data Analysis and Classification,Vol. 5, No. 1, Pp. 23-36, 2011.03, Papers

  20. Joint Procrustes Analysis for Simultaneous Nonsingular Transformation of Component Score and Loading Matrices, Kohei Adachi, Psychometrika,Vol. 74, 667-683, 2009.12, Papers

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