Работа посвящена развитию алгоритмов обучения нейронных сетей прямого распространения на основе нелинейного метода наименьших квадратов с псевдообращением....

Partial least squares-based path modeling with latent variables is a methodology that allows to estimate complex cause-effect relationships using empirical data. The assumption that the data is collected from a single homogeneous population is often unrealistic. Identification of different...

This paper proposes a nonparametric simultaneous test for parametric specification of the conditional mean and variance functions in a time series regression model. The test is based on an empirical likelihood (EL) statistic that measures the goodness-of-fit between the parametric estimates and...

We propose a new method to estimate a repeat-sales house price index. Our unbalanced panel method employs an OLS panel regression to estimate the (log) house price as a function of time fixed effects and house-specific fixed effects. Comparisons are made across three repeat-sales methods using...

In this paper we present, propose and examine additional membership functions as also we propose least squares with genetic algorithms optimization in order to find the optimum fuzzy membership functions parameters. More specifically, we present the tangent hyperbolic, Gaussian and Generalized...

Partial least squares analysis is a multivariate statistical technique that allows comparison between multiple response variables and multiple explanatory variables. Partial least squares is one of a number of covariance-based statistical methods which are often referred to as structural...

This paper tests empirically the recently proposed canonical least-squares Monte-Carlo (CLM) method for pricing American options. Market data used are daily last prices for the American style S&P 100 Index puts (OEX puts) and IBM puts from 30 July 2008 to 30 January 2009, the period of which...

This paper considers estimation situations where identification, endogeneity and non-spherical regression error problems are present. Instead of always using GMM despite weak instruments to solve the endogeneity, it is possible to first check whether endogeneity is serious enough to cause...