If in the linear model （1）the random errors e<sub>1</sub>, e<sub>2</sub>,...satisfy assumption （B） （See Section 1）, then a necessary condition for the consistency of the LAD estimate of ...If in the linear model （1）the random errors e<sub>1</sub>, e<sub>2</sub>,...satisfy assumption （B） （See Section 1）, then a necessary condition for the consistency of the LAD estimate of β<sub>o</sub> is sum from i=1 to∞‖xi‖<sup>2</sup>=∞.展开更多
By employing the empirical likelihood method, confidence regions for the stationary AR（p）-ARCH（q） models are constructed. A self-weighted LAD estimator is proposed under weak moment conditions. An empirical log-li...By employing the empirical likelihood method, confidence regions for the stationary AR（p）-ARCH（q） models are constructed. A self-weighted LAD estimator is proposed under weak moment conditions. An empirical log-likelihood ratio statistic is derived and its asymptotic distribution is obtained. Simulation studies show that the performance of empirical likelihood method is better than that of normal approximation of the LAD estimator in terms of the coverage accuracy, especially for relative small size of observation.展开更多
Let Yi=x'iβo+ei. 1≤i≤n, n≥1 be a linear regression model. Denote by βn the M-estimateof βo, using a convex function ρ. In [1], a basic theorem (Theorem A below) concerning the weakconsistency of βn. is est...Let Yi=x'iβo+ei. 1≤i≤n, n≥1 be a linear regression model. Denote by βn the M-estimateof βo, using a convex function ρ. In [1], a basic theorem (Theorem A below) concerning the weakconsistency of βn. is established. This theorem raises further questions concerning the consistencyof βn. In this note, some of these questions are considered for the special cases of LAD and LSestimates.展开更多
基金Supported by the National Natural Sciences Foundation of China.
文摘If in the linear model （1）the random errors e<sub>1</sub>, e<sub>2</sub>,...satisfy assumption （B） （See Section 1）, then a necessary condition for the consistency of the LAD estimate of β<sub>o</sub> is sum from i=1 to∞‖xi‖<sup>2</sup>=∞.
基金Supported by the Fundamental Research Funds for the Central Universities (No. 2010LKSX04)Supported by the National Natural Science Foundation of China (No. 10731010)
文摘By employing the empirical likelihood method, confidence regions for the stationary AR（p）-ARCH（q） models are constructed. A self-weighted LAD estimator is proposed under weak moment conditions. An empirical log-likelihood ratio statistic is derived and its asymptotic distribution is obtained. Simulation studies show that the performance of empirical likelihood method is better than that of normal approximation of the LAD estimator in terms of the coverage accuracy, especially for relative small size of observation.
文摘Let Yi=x'iβo+ei. 1≤i≤n, n≥1 be a linear regression model. Denote by βn the M-estimateof βo, using a convex function ρ. In [1], a basic theorem (Theorem A below) concerning the weakconsistency of βn. is established. This theorem raises further questions concerning the consistencyof βn. In this note, some of these questions are considered for the special cases of LAD and LSestimates.
