This paper uses a grouping-adjusting procedure to the data from a median linear regression model, and estimtes the regression coefficients by the method of weighted least squares. This method simplifies computation an...This paper uses a grouping-adjusting procedure to the data from a median linear regression model, and estimtes the regression coefficients by the method of weighted least squares. This method simplifies computation and in the meantime, preserves the same asymptotic normal distribution for the estimator, as in the ordinary minimum L_1-norm estimates.展开更多
Natural resource statistics are often unavailable for small ecological or economic regions and policymakers have to rely on state-level datasets to evaluate the status of their resources （i.e., forests, rangelands, g...Natural resource statistics are often unavailable for small ecological or economic regions and policymakers have to rely on state-level datasets to evaluate the status of their resources （i.e., forests, rangelands, grasslands, agriculture, etc.） at the regional or local level. These resources can be evaluated using small-area estimation techniques. However, it is unknown which small area technique produces the most valid and precise results. The reliability and accuracy of two methods, synthetic and regression estimators, used in smallarea analyses, were examined in this study. The two small-area analysis methods were applied to data from Jalisco＇s state-wide natural resource inventory to examine how well each technique predicted selected characteristics of forest stand structure. The regression method produced the most valid and precise estimates of forest stand characteristics at multiple geographical scales. Therefore, state and local resource managers should utilize the regression method unless appropriate auxiliary information is not available.展开更多
The application of low complexity and low order robust regression algorithm in channel estimation with 16QAM over fading channel for DS-CDMA is presented in this paper After initial channel estimation with classical m...The application of low complexity and low order robust regression algorithm in channel estimation with 16QAM over fading channel for DS-CDMA is presented in this paper After initial channel estimation with classical methods, channel gains estimated are filtered by linear or conic regression algorithm within a given regression length Simulation results show that this method offers up to 0,3 dB gain in a DS-CDMA system. The length and order of regression algorithm are two key parameters, which affect the system performance significantly and the optimal values of which depend on the speed of mobile station. It is demonstrated that this improved method can track fading channel accurately and outperforms over classical methods substantially by selecting appropriate parameters of regression algorithm under a certain channel environment.展开更多
基金Research supported By AFOSC, USA, under Contract F49620-85-0008oy NNSFC of China.
文摘This paper uses a grouping-adjusting procedure to the data from a median linear regression model, and estimtes the regression coefficients by the method of weighted least squares. This method simplifies computation and in the meantime, preserves the same asymptotic normal distribution for the estimator, as in the ordinary minimum L_1-norm estimates.
文摘Natural resource statistics are often unavailable for small ecological or economic regions and policymakers have to rely on state-level datasets to evaluate the status of their resources （i.e., forests, rangelands, grasslands, agriculture, etc.） at the regional or local level. These resources can be evaluated using small-area estimation techniques. However, it is unknown which small area technique produces the most valid and precise results. The reliability and accuracy of two methods, synthetic and regression estimators, used in smallarea analyses, were examined in this study. The two small-area analysis methods were applied to data from Jalisco＇s state-wide natural resource inventory to examine how well each technique predicted selected characteristics of forest stand structure. The regression method produced the most valid and precise estimates of forest stand characteristics at multiple geographical scales. Therefore, state and local resource managers should utilize the regression method unless appropriate auxiliary information is not available.
文摘The application of low complexity and low order robust regression algorithm in channel estimation with 16QAM over fading channel for DS-CDMA is presented in this paper After initial channel estimation with classical methods, channel gains estimated are filtered by linear or conic regression algorithm within a given regression length Simulation results show that this method offers up to 0,3 dB gain in a DS-CDMA system. The length and order of regression algorithm are two key parameters, which affect the system performance significantly and the optimal values of which depend on the speed of mobile station. It is demonstrated that this improved method can track fading channel accurately and outperforms over classical methods substantially by selecting appropriate parameters of regression algorithm under a certain channel environment.
