Currently browsing: Items authored or edited by Nickolay Trendafilov https://orcid.org/0000-0001-9309-1375

Unkel, Steffen and Trendafilov, Nickolay (2009). Factor analysis as data matrix decomposition: a new approach for quasi-sphering in noisy ICA. In: Adali, Tülay; Jutten, Christian; Romano, João MarcosTravassos and Barros, Allan Kardec eds. Independent Component Analysis and Signal Separation: 8th International Conference, ICA 2009, Paraty, Brazil, March 15-18, 2009. Proceedings. Lecture Notes in Computer Science (5441). Berlin: Springer, pp. 163–170.

Unkel, Steffen and Trendafilov, Nickolay T (2007). Noisy independent component analysis as a method of rotating the factor scores. In: Davies, Mike E; James, Christopher J; Abdallah, Samer A and Plumbley, Mark D eds. Independent Component Analysis and Signal Separation: 7th International Conference, ICA 2007, London, UK, September 9-12, 2007. Proceedings. Lecture Notes in Computer Science (4666). Berlin: Springer, pp. 810–817.

Joliffe, I.T.; Learmouth, J.A.; Pierce, G.J.; Santos, M.B.; Trendafilov, N.; Zuur, A.F.; Ieno, E.N. and Smith, G.M. (2007). Principal component analysis applied to harbour porpoise fatty acid data. In: Zuur, Alain F.; Ieno, Elena N. and Smith, Graham M. eds. Analysing Ecological Data. Statistics for biology and health. New York: Springer, pp. 515–528.

Bartkowiak, Anna and Trendafilov, Nickolay (2005). Feature extraction by the SCoTLASS: an illustrative example. In: Klopotek, Mieczyslaw A; Wierzchen, Slawomir T. and Trojanowski, Krzysztof eds. Intelligent Information Processing and Web Mining. Advances in Intelligent and Soft Computing (31). Berlin: Springer, pp. 3–11.

Adachi, Kohei and Trendafilov, Nickolay T. (2019). Some inequalities contrasting principal component and factor analyses solutions. Japanese Journal of Statistics and Data Science, 2(1) pp. 31–47.

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Eldén, Lars and Trendafilov, Nickolay (2019). Semi-sparse PCA. Psychometrika, 84(1) pp. 164–185.

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Trendafilov, Nickolay T. and Fontanella, Sara (2019). Exploratory factor analysis of large data matrices. Statistical Analysis and Data Mining, 12(1) pp. 5–11.

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Fontanella, Lara; Fontanella, Sara; Valentini, Pasquale and Trendafilov, Nickolay (2019). Simple Structure Detection Through Bayesian Exploratory Multidimensional IRT Models. Multivariate Behavioral Research, 54(1) pp. 100–112.

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Uno, Kohei; Adachi, Kohei and Trendafilov, Nickolay T. (2019). Clustered Common Factor Exploration in Factor Analysis. Psychometrika, 84(4) pp. 1048–1067.

Adachi, Kohei and Trendafilov, Nickolay T. (2018). Sparsest factor analysis for clustering variables: a matrix decomposition approach. Advances in Data Analysis and Classification, 12(3) pp. 559–585.

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Adachi, Kohei and Trendafilov, Nickolay (2018). Some Mathematical Properties of the Matrix Decomposition Solution in Factor Analysis. Psychometrika, 83(2) pp. 407–424.

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Hannachi, A. and Trendafilov, N. (2017). Archetypal Analysis: Mining Weather and Climate Extremes. Journal of Climate, 30(17) pp. 6927–6944.

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Trendafilov, Nickolay T.; Fontanella, Sara and Adachi, Kohei (2017). Sparse Exploratory Factor Analysis. Psychometrika, 82(3) pp. 778–794.

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Adachi, Kohei and Trendafilov, Nickolay T. (2016). Sparse principal component analysis subject to prespecified cardinality of loadings. Computational Statistics, 31(4) pp. 1403–1427.

Gallo, Michele; Trendafilov, Nickolay and Buccianti, Antonella (2016). Sparse PCA and investigation of multielements compositional repositories: theory and applications. Environmental and Ecological Statistics, 23(3) pp. 421–434.

Trendafilov, Nickolay T. and Gebru, Tsegay Gebrehiwot (2016). Recipes for sparse LDA of horizontal data. METRON, 74 pp. 207–221.

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Trendafilov, Nickolay T. and Adachi, Kohei (2015). Sparse versus simple structure loadings. Psychometrika, 80(3) pp. 776–790.

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Trendafilov, Nickolay T. (2014). From simple structure to sparse components: a review. Computational Statistics, 29(3-4) pp. 431–454.

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Trendafilov, Nickolay; Kleinsteuber, Martin and Zou, Hui (2014). Sparse matrices in data analysis. Computational Statistics, 29(3-4) pp. 403–405.

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Enki, Doyo G.; Trendafilov, Nickolay T. and Jolliffe, Ian T. (2013). A clustering approach to interpretable principal components. Journal of Applied Statistics, 40(3) pp. 583–599.

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Trendafilov, Nickolay; Unkel, Steffen and Krzanowski, Wojtek (2013). Exploratory factor and principal component analyses: some new aspects. Statistics and Computing, 23(2) pp. 209–220.

Unkel, Steffen and Trendafilov, Nickolay T. (2013). Zig-zag exploratory factor analysis with more variables than observations. Computational Statistics, 28(1) pp. 107–125.

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Trendafilov, Nickolay (2012). Dindscal: direct INDSCAL. Statistics and Computing, 22(2) pp. 445–454.

Enki, Doyo G. and Trendafilov, Nickolay T. (2012). Sparse principal components by semi-partition clustering. Computational Statistics, 27(4) pp. 605–626.

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Unkel, Steffen; Hannachi, Abdel; Trendafilov, Nickolay T. and Jolliffe, Ian T. (2011). Independent component analysis for three-way data with an application from atmospheric science. Journal of Agricultural, Biological, and Environmental Statistics, 16(3) pp. 319–338.

Trendafilov, Nickolay T. and Unkel, Steffen (2011). Exploratory factor analysis of data matrices with more variables than observations. Journal of Computational and Graphical Statistics, 20(4) pp. 874–891.

Unkel, S. and Trendafilov, N. T. (2010). A majorization algorithm for simultaneous parameter estimation in robust exploratory factor analysis. Computational Statistics and Data Analysis, 54(12) pp. 3348–3358.

Trendafilov, Nickolay (2010). Stepwise estimation of common principal components. Computational Statistics and Data Analysis, 54(12) pp. 3446–3457.

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Unkel, Steffen; Trendafilov, Nickolay T.; Hannachi, Abdel and Jolliffe, Ian T. (2010). Independent exploratory factor analysis with application to atmospheric science data. Journal of Applied Statistics, 37(11) pp. 1847–1862.

Kostova, Snezhanka; Trendafilov, Nickolay; Popova, Silviya and Georgieva, Nonka (2010). Eco-effcency: concept, approaches and assessment. Bulgarian Journal of Meteorology and Hydrology, 15(1) pp. 118–128.

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Unkel, Steffen and Trendafilov, Nickolay T. (2010). Simultaneous parameter estimation in exploratory factor analysis: an expository review. International Statistical Review, 78(3) pp. 363–382.

Kostova, Snezhanka; Trendafilov, Nickolay; Popova, Silviya and Georgieva, Nonka (2010). Eco-efficiency: concept, approaches and assessment. Bulgarian Journal of Meteorology and Hydrology, 15(1) pp. 118–128.

Hannachi, A.; Unkel, S.; Trendafilov, N. T. and Joliffe, I. T. (2009). Independent component analysis of climate data: a new look at EOF rotation. Journal of Climate, 22(11) pp. 2797–2812.

Trendafilov, N. T. and Vines, K. (2009). Simple and interpretable discrimination. Computational Statistics and Data Analysis, 53(4) pp. 979–989.

Trendafilov, Nickolay T. and Jolliffe, Ian T. (2007). DALASS: Variable selection in discriminant analysis via the LASSO. Computational Statistics and Data Analysis, 51(8) pp. 3718–3736.

Trendafilov, Nickolay T. (2006). The Dynamical System Approach to Multivariate Data Analysis. Journal of Computational and Graphical Statistics, 15(3) pp. 628–650.

Trendafilov, Nickolay T. and Jolliffe, Ian T. (2006). Projected gradient approach to the numerical solution of the SCoTLASS. Computational Statistics and Data Analysis, 50(1) pp. 242–253.

Hannachi, A.; Jolliffe, I. T.; Stephenson, D. B. and Trendafilov, N. (2006). In search of simple structures in climate: Simplifying EOFs. International Journal of Climatology, 26(1) pp. 7–28.

Jennrich, Robert I. and Trendafilov, Nickolay T. (2005). Independent component analysis as a rotation method: A very different solution to Thurstone's box problem. British Journal of Mathematical and Statistical Psychology, 58(2) pp. 199–208.

Trendafilov, Nickolay T. (2005). Fitting the factor analysis model in ℓ₁ norm. British Journal of Mathematical and Statistical Psychology, 58(1) pp. 19–31.

Trendafilov, Nickolay T. and Watson, G. A. (2004). The ℓ 1 oblique procrustes problem. Statistics and Computing, 14(1) pp. 39–51.

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Jolliffe, I.T.; Trendafilov, N.T. and Uddin, M. (2003). A modified principal component technique based on the LASSO. Journal of Computational and Graphical Statistics, 12(3) pp. 531–547.

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Trendafilov, Nickolay T. (2003). Dynamical system approach to factor analysis parameter estimation. British Journal of Mathematical and Statistical Psychology, 56(1) pp. 27–46.

Trendafilov, Nickolay T. (2003). On the ℓ₁ Procrustes problem. Future Generation Computer Systems, 19(7) pp. 1177–1186.

Trendafilov, Nickolay T. and Lippert, Ross A. (2002). The multimode Procrustes problem. Linear Algebra and its Applications, 349(1-3) pp. 245–264.

Trendafilov, Nickolay T. (2002). GIPSCAL revisited. A projected gradient approach. Statistics and Computing, 12(2) pp. 135–145.

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Chu, M.T. and Trendafilov, N.T. (2001). The orthogonally constrained regression revisited. Journal of Computational and Graphical Statistics, 10(4) pp. 746–771.

Trendafilov, Nickolay T. (1999). A continuous-time approach to the oblique Procrustes problem. Behaviormetrika, 26(2) pp. 167–181.

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Trendafilov, Nickolay T. and Chu, Moody T. (1998). On a differential equation approach to the weighted orthogonal Procrustes problem. Statistics and Computing, 8(2) pp. 125–133.

Trendafilov, Nickolay T. and Chu, Moody T. (1998). ORTHOMAX rotation problem. a differential equation approach. Behaviormetrika, 25(1) pp. 13–23.

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Trendafilov, Nickolay (1996). Iterative majorizing rotation to orthogonal simple structure solution. Multivariate Behavioral Research, 31(3) pp. 271–287.

Trendafilov, Nickolay (1994). A simple method for procrustean rotation in factor analysis using majorization theory. Multivariate Behavioral Research, 29(4) pp. 385–408.

Fontanella, Sara; Trendafilov, Nickolay and Adachi, Kohei (2014). Sparse exploratory factor analysis. In: Proceedings of COMPSTAT 2014: 21st International Conference on Computational Statistics, pp. 281–288.

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Trendafilov, Nickolay and Adachi, Kohei (2014). Penalty-free sparse PCA. In: Proceedings of COMPSTAT 2014: 21st International Conference on Computational Statistics, pp. 197–203.

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Trendafilov, Nickolay (2004). Orthonormality-constrained INDSCAL with nonnegative saliences. In: Computational Science and Its Applications - ICCSA 2004 (Lagan'a, Antonio; Gavrilova, Marina L.; Kumer, Vipin; Mun, Youngsong; Kenneth Tan, C. J. and Gervasi, Osvaldo eds.), Lecture Notes in Computer Science, Springer, Berlin, Germany, pp. 952–960.