Academic Papers

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  1. Some Mathematical Properties of the Matrix Decomposition Solution in Factor Analysis , Kohei Adachi & Nickolay T. Trendafilov, Psychometrika,https://doi.org/10.1007/s11336-017-9600-y, 2017.12, Papers

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

  3. Sparsest factor analysis for clustering variables: A matrix decomposition approach, Kohei Adachi & Nickolay T. Trendafilov, Advances in Data Analysis and Classification,(in Press) available as 'Online First': http://link.springer.com/article/10.1007/s11634-017-0284-z, 2017.04, Papers

  4. 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

  5. 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

  6. Fixed factor analysis with clustered factor score constraint, Kohei Uno, Hironori Satomura, Kohei Adachi, Computational Statistics and Data Analysis,in Press, 2016.03, Papers

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

  8. 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

  9. 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

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

  11. 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

  12. 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

  13. 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

  14. 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

  15. 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

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

  17. Trend Vector Representation of Multiple Transition Matrices by Penalized Optimal Scaling, Kohei Adachi, Journal of the Japanese Society of Computational Statistics,Vol. 20, No. 1, pp. 19-37, 2007.12, Papers

  18. Correct Classification Rates in Multiple Correspondence Analysis, K. Adachi, Journal of the Japanese Society of Computational Statistics,Vol. 17, 1-20, 2005.05, Papers

  19. Oblique Promax Rotation Applied to the Solutions in Multiple Correspondence Analysis, K. Adachi, Behaviormetrika,Vol. 31 (No. 2), 1-12, 2004.09, Papers

  20. Optimal Quantification of a Longitudinal Indicator Matrix: Homogeneity and Smoothness Analysis, K. Adachi, Journal of Classification,Vol.19 (No.2) 215-248, 2002.11, Papers

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