Nonparametric analysis of stochastic systems with nonlinear functional heterogeneity

Vladimir Malugin and Mikhail Vasilkov ()
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Mikhail Vasilkov: Belarusian State University

Applied Econometrics, 2011, vol. 22, issue 2, 78-92

Abstract: The problems of the analysis of stochastic systems described by nonlinear statistical models with heterogeneous functional forms are considered in the space of «essential dependent» features. It is supposed that functional heterogeneity is conditioned by the existing of the different classes of system states. The algorithm of classification of the systems states as well as the forecasting algorithm for endogenous variables based on multivariate nonparametric density estimate with adaptive kernel are described and examined by means of statistical modeling experiments

Keywords: multivariate model; essential dependent features; functional heterogeneity; multivariate nonparametric density estimate; adaptive Gaussian kernel; nonparametric classification and forecasting (search for similar items in EconPapers)
JEL-codes: C14 C38 (search for similar items in EconPapers)
Date: 2011
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