Information Criteria for Discriminating Among Alternative Regression Models
نویسندگان
چکیده
منابع مشابه
Exponentially Weighted Information Criteria for Selecting Among Forecasting Models
Information criteria (IC) are often used to select between forecasting models. Commonly used criteria are Akaike’s IC and Schwarz’s Bayesian IC. They involve the sum of two terms: the model’s log likelihood and a penalty for the number of model parameters. The likelihood is calculated with equal weight given to all observations. We propose that greater weight should be put on more recent observ...
متن کاملEstimation of B-spline Nonparametric Regression Models using Information Criteria
Nonparametric regression modelling has received considerable attention and many methods have been proposed to draw information from data with complex structure. We consider the use of B-spline nonparametric regression models estimated by penalized likelihood methods. A crucial point in constructing the models is in the choice of a smoothing parameter and the number of knots, for which several a...
متن کاملT-optimal discriminating designs for Fourier regression models
In this paper we consider the problem of constructing T -optimal discriminating designs for Fourier regression models. We provide explicit solutions of the optimal design problem for discriminating between two Fourier regression models, which differ by at most three trigonometric functions. In general, the T -optimal discriminating design depends in a complicated way on the parameters of the la...
متن کاملRidge Regression under Alternative Loss Criteria
T HE introduction by Hoerl and Kennard (1970) of a ridge regression estimator to deal with the problem of multicollinearity in regression has been followed by a large number of papers in the statistical literature. In the area of econometrics, though, the method of ridge regression has received little attention. I One of the reasons for the lack of interest in ridge regression on the part of th...
متن کاملOptimal discriminating designs for several competing regression models
The problem of constructing optimal designs for a class of regression models is considered. We investigate a version of the Tp-optimality criterion as introduced by Atkinson and Fedorov (1975b) and demonstrate that optimal designs with respect to this type of criteria can be obtained by solving (nonlinear) vector-valued approximation problems. We provide a characterization of the best approxima...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Econometrica
سال: 1978
ISSN: 0012-9682
DOI: 10.2307/1913828