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Sociological Methods & Research, 1986
Measurement errors in predictor variables bias multiple regression coefficients, and the problem is particularly complex with nonlinear models containing product variates. This article presents formulas and computing algorithms for correcting data before regression analyses in order to eliminate biases due to measurement errors in models with second ...
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Measurement errors in predictor variables bias multiple regression coefficients, and the problem is particularly complex with nonlinear models containing product variates. This article presents formulas and computing algorithms for correcting data before regression analyses in order to eliminate biases due to measurement errors in models with second ...
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IFAC Proceedings Volumes, 1985
Abstract In this paper the problem of obtaining state estimates for nonlinear, dynamic, stochastic systems is investigated. Recursive algorithms are introduced which, given a sequence of noisy measurements of the system output, produce optimal estimates of the system state for a specified optimality criterion.
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Abstract In this paper the problem of obtaining state estimates for nonlinear, dynamic, stochastic systems is investigated. Recursive algorithms are introduced which, given a sequence of noisy measurements of the system output, produce optimal estimates of the system state for a specified optimality criterion.
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Nonlinear Filter Estimation of Volatility
Stochastic Analysis and Applications, 2010A discrete time nonlinear filter is used to estimate the volatility in a financial model. New filters are derived for sums of unobserved quantities and the EM algorithm applied to determine the parameters of the model.
Elliott, R. +2 more
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Parameter Estimation in Nonlinear Regression
Calcutta Statistical Association Bulletin, 1990ABSTRACT: A restriction generally imposed when proving consistency results in nonlinear regression is that the parameter space be compact. The authors relax this assumption; indeed, the parameter space includes all separable metric spaces. A nonlinear regression model having random regressors is studied.
Bhattacharyya, B. B., Richardson, G. D.
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Measure of Nonlinearity for Estimation
IEEE Transactions on Signal Processing, 2015zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Liu, Yu, Li, X. Rong
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ESTIMATION OF NONLINEAR ERROR CORRECTION MODELS [PDF]
Econometric Theory, 2010 Asymptotic theory for the estimation of nonlinear vector error correction models that exhibit regime-specific short-run dynamics is developed. In particular, regimes are determined by the error correction term, and the transition between regimes is allowed to be discontinuous, as in, e.g., threshold cointegration.
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Nonlinear estimation techniques
IEEE Transactions on Automatic Control, 1968This paper considers a discrete real-time nonlinear estimation problem using a least-square criterion. A sequential algorithm is derived which allows consideration of second-order nonlinearities in system measurements. Alternate nonlinear estimation techniques are discussed and examples are given which compare the various estimation algorithms.
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Nonlinear Extrapolation Estimates of π
Acta Mathematicae Applicatae Sinica, English SerieszbMATH Open Web Interface contents unavailable due to conflicting licenses.
Xu, Wen-qing +2 more
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