Results 141 to 150 of about 124,454 (198)

Heteroscedastic factor analysis

Biometrika, 2003
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Lewin-Koh, S.-C., Amemiya, Y.
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Heteroscedastic Exponomial Choice

Operations Research, 2018
Modeling Choices with Different Variabilities
Aydın Alptekinoğlu, John H. Semple
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Heteroscedastic factor mixture analysis

Statistical Modelling, 2010
When data come from an unobserved heterogeneous population, common factor analysis is not appropriate to estimate the underlying constructs of interest. By replacing the traditional assumption of Gaussian distributed factors by a finite mixture of multivariate Gaussians, the unobserved heterogeneity can be modelled by latent classes.
MONTANARI, ANGELA, VIROLI, CINZIA
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Gaussian Process-Mixture Conditional Heteroscedasticity

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2014
Generalized autoregressive conditional heteroscedasticity (GARCH) models have long been considered as one of the most successful families of approaches for volatility modeling in financial return series. In this paper, we propose an alternative approach based on methodologies widely used in the field of statistical machine learning.
Platanios, Emmanouil Antonios, Chatzis, Sotirios P.   +1 more
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Heteroscedasticity and nonnormality

Communications in Partial Differential Equations, 1989
In this paper we consider the problem of comparing several means under heteroscedasticity and nonnormality. By combining Huber's M-estimators with the Brown-Forsythe test , several robust procedures were developed; these procedures were compared through computer simulation studies with-the Tan-Tabatabai procedure which was developed by combining Tiku's
W. Y. Tan, M. A. Tabatabai
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Stock Prices and Heteroscedasticity

The Journal of Business, 1976
This paper provides evidence that the variance of returns on common stocks is not constant through time but is related to the volume of shares traded. In other words, returns on stocks are heteroscedastic. The work extends the approaches of Osborne, Granger and Morgenstern, and Clark.' Distributions of returns are known to be leptokurtic.
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Heteroscedastic Nonlinear Regression

Technometrics, 1988
Several parameter estimation methods for dealing with heteroscedasticity in nonlinear regression are described. These include variations on ordinary, weighted, iteratively reweighted, extended. and generalized least squares. Some of these variations are new, and one of them in particular, modified extended iteratively reweighted least squares (MEIRLS),
S. L. Beal, L. B. Sheiner
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