Results 1 to 10 of about 194,565 (112)
Spurious Factor Analysis [PDF]
Econometrica, 2021 This paper draws parallels between the principal components analysis of factorless high‐dimensional nonstationary data and the classical spurious regression. We show that a few of the principal components of such data absorb nearly all the data variation.
Onatskiy, Alexey, Wang, Chen
openaire +3 more sources
Phylogenetic Factor Analysis [PDF]
Systematic Biology, 2017 51 pages (42 main, 9 supplemental), 9 figures (5 main, 4 supplemental), 4 tables (2 main, 2 supplemental), submitted to Systematic ...
Tolkoff, Max R +4 more
openaire +6 more sources
Expandable factor analysis [PDF]
Biometrika, 2017 28 pages, 4 ...
Barbara E. Engelhardt +2 more
openaire +3 more sources
Multimodal factor analysis [PDF]
2015 IEEE 25th International Workshop on Machine Learning for Signal Processing (MLSP), 2015 A multimodal system with Poisson, Gaussian, and multinomial observations is considered. A generative graphical model that combines multiple modalities through common factor loadings is proposed. In this model, latent factors are like summary objects that has latent factor scores in each modality, and the observed objects are represented in terms of ...
Alfred O. Hero, Yasin Yilmaz
openaire +3 more sources
IEEE Transactions on Neural Networks and Learning Systems, 2015 Factor analysis provides linear factors that describe relationships between individual variables of a data set. We extend this classical formulation into linear factors that describe relationships between groups of variables, where each group represents either a set of related variables or a data set.
Klami, Arto +4 more
openaire +9 more sources
Multilingual Factor Analysis [PDF]
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 2019 In this work we approach the task of learning multilingual word representations in an offline manner by fitting a generative latent variable model to a multilingual dictionary. We model equivalent words in different languages as different views of the same word generated by a common latent variable representing their latent lexical meaning.
Francisco Vargas +3 more
openaire +3 more sources
Bayesian exploratory factor analysis [PDF]
Journal of Econometrics, 2014 This paper develops and applies a Bayesian approach to Exploratory Factor Analysis that improves on ad hoc classical approaches. Our framework relies on dedicated factor models and simultaneously determines the number of factors, the allocation of each measurement to a unique factor, and the corresponding factor loadings.
Conti, Gabriella +3 more
openaire +15 more sources
Journal of Multivariate Analysis, 2003 AbstractOur aim is to construct a factor analysis method that can resist the effect of outliers. For this we start with a highly robust initial covariance estimator, after which the factors can be obtained from maximum likelihood or from principal factor analysis (PFA).
Pison, Greet +3 more
openaire +4 more sources
Conditions for Factor (in)Determinacy in Factor Analysis [PDF]
Psychometrika, 1998 The subject of factor indeterminacy has a vast history in factor analysis (Guttman, 1955; Lederman, 1938; Wilson, 1928). It has lead to strong differences in opinion (Steiger, 1979). The current paper gives necessary and sufficient conditions for observability of factors in terms of the parameter matrices and a finite number of variables.
Krijnen, W.P. +2 more
openaire +4 more sources
, 2013 Factor analysis is a multivariate statistical method for data reduction that originated in psychometrics and has found applications in many branches of science. The method aims to describe the correlation structure between a large set of observed variables in terms of a few underlying latent variables called factors.
openaire +4 more sources