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Model averaging by jackknife criterion in models with dependent data

依赖数据模型中基于刀切准则的模型平均

The past decade witnessed a literature on model averaging by frequentist methods. For the most part, the asymptotic optimality of various existing frequentist model averaging estimators has been established under i.i.d. errors. Recently, Hansen and Racine [Hansen, B.E., Racine, J., 2012. Jackknife model averaging. Journal of Econometrics 167, 38–46] developed a jackknife model averaging (JMA) estimator, which has an important advantage over its competitors in that it…

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Wavelet analysis of change-points in a non-parametric regression with heteroscedastic variance

异方差非参数回归中变点的小波分析

In this paper we develop wavelet methods for detecting and estimating jumps and cusps in the mean function of a non-parametric regression model. An important characteristic of the model considered here is that it allows for conditional heteroscedastic variance, a feature frequently encountered with economic and financial data. Wavelet analysis of change-points in this model has been considered in a limited way in a recent study by Chen et al. (2008) with a focus on jumps…

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Least squares model averaging by Mallows criterion

基于 Mallows 准则的最小二乘模型平均

This paper is in response to a recent paper by Hansen (2007) who proposed an optimal model average estimator with weights selected by minimizing a Mallows criterion. The main contribution of Hansen's paper is a demonstration that the Mallows criterion is asymptotically equivalent to the squared error, so the model average estimator that minimizes the Mallows criterion also minimizes the squared error in large samples. We are concerned with two assumptions that accompany…

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On the sensitivity of the restricted least squares estimators to covariance misspecification

受限最小二乘估计量对协方差误设的敏感性

Traditional econometrics has long stressed the serious consequences of non-spherical disturbances for the estimation and testing procedures under the spherical disturbance setting, that is, the procedures become invalid and can give rise to misleading results. In practice, it is not unusual, however, to find that the parameter estimates do not change much after fitting the more general structure. This suggests that the usual procedures may well be robust to covariance…

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Further results on optimal critical values of pre‐test when estimating the regression error variance

回归误差方差估计中预检验最优临界值的进一步结果

This paper enlarges on results of Wan and Zou (Journal of Econometrics 114 (2003), 165--96) on the choice of critical values for pre-test procedures based on the minimum risk criterion. We consider a modification of the general theorem given in Wan and Zou (2003) to obtain the optimal critical value that minimizes the risks of various inequality pre-test estimators of the regression error variance under a general class of first-order differentiable loss functions.…

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ON THE PROPERTIES OF THE t- AND F-RATIOS IN LINEAR REGRESSIONS WITH NONNORMAL ERRORS

非正态误差线性回归中 t 比率与 F 比率的性质

In this paper we derive the necessary and sufficient conditions for the t-ratio to be Student's t distributed. In particular, it is demonstrated for a special case that under conditions of nonnormality characterized by elliptical symmetry, the t-ratio remains Student's t distributed provided that the random vector forming the t-ratio has a diagonal covariance structure. Our results also show that the findings of Magnus (2002, in A. Ullah, A.T.K. Wan, & A. Chaturvedi (eds.),…

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