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Consistency of M estimates for separable nonlinear regression models
Nonlinear regression separable models con-sistency robust estimation.
2012/9/18
Consider a nonlinear regression model :yi =g(xi, 兤) +ei, i = 1, ..., n,where thexi are random predictorsxi and兤is the unknown parameter vector ranging in a set set 儲伡Rp. All known results on the consi...
上海财经大学经济学院高级计量经济学I课件Lecture 4 Nonlinear Regression Models and Generalized Least Squares
上海财经大学经济学院 高级计量经济学I 课件 Lecture 4 Regression Models Generalized Least Squares
2012/7/16
上海财经大学经济学院高级计量经济学I课件Lecture 4 Nonlinear Regression Models and Generalized Least Squares.
Robust M-Procedures in Univariate Nonlinear Regression Models
Robust M-Procedures Univariate Nonlinear Regression Models
2009/9/17
Robust M-Procedures in Univariate Nonlinear Regression Models。
Birnbaum-Saunders nonlinear regression models
Bias correction Birnbaum–Saunders distribution maximumlikelihood estimation nonlinear regression
2010/3/17
We introduce, for the first time, a new class of Birnbaum–Saunders nonlinear
regression models potentially useful in lifetime data analysis. The class generalizes
the regression model described by R...
Parameter estimation for computationally intensive nonlinear regression with an application to climate modeling
Equilibrium climate sensitivity observed and modeled climate space–time modeling statistical surrogate temperature data
2010/3/17
Nonlinear regression is a useful statistical tool, relating observed
data and a nonlinear function of unknown parameters. When the
parameter-dependent nonlinear function is computationally intensive...