[Objective] This study aimed to explore the impact of climate change on wheat cropping by using province-specific historical data during 1996-2007. [Method] We established a panel data econometric model with lagged wh...[Objective] This study aimed to explore the impact of climate change on wheat cropping by using province-specific historical data during 1996-2007. [Method] We established a panel data econometric model with lagged wheat cropping area and province-specific fixed-effects model to control the unobserved factors. [Result] The results showed that the temperature positively affects wheat cropping area, while precipitation does not have such impact. [Conclusion] The study provided empirical evidence for analysis of the determinants of wheat cropping area in China.展开更多
This paper investigates the scaled prediction variances in the errors-in-variables model and compares the performance with those in classic model of response surface designs for three factors.The ordinary least square...This paper investigates the scaled prediction variances in the errors-in-variables model and compares the performance with those in classic model of response surface designs for three factors.The ordinary least squares estimators of regression coefficients are derived from a second-order response surface model with errors in variables.Three performance criteria are proposed.The first is the difference between the empirical mean of maximum value of scaled prediction variance with errors and the maximum value of scaled prediction variance without errors.The second is the mean squared deviation from the mean of simulated maximum scaled prediction variance with errors.The last performance measure is the mean squared scaled prediction variance change with and without errors.In the simulations,1 000 random samples were performed following three factors with 20 experimental runs for central composite designs and 15 for Box-Behnken design.The independent variables are coded variables in these designs.Comparative results show that for the low level errors in variables,central composite face-centered design is optimal;otherwise,Box-Behnken design has a relatively better performance.展开更多
Objective To identify clinical characteristics associated with the minimum lumen area （MLA） of proximal or middle intermediate lesions in the left anterior descending （LAD） artery, and to develop a model to predic...Objective To identify clinical characteristics associated with the minimum lumen area （MLA） of proximal or middle intermediate lesions in the left anterior descending （LAD） artery, and to develop a model to predict MLA. Methods We retrospectively analyzed demographic data, medical history, and intravascular ultrasound findings for 90 patients with intermediate lesions in the LAD artery. Linear regression was used to identify factors affecting MLA, and multiple regression was used to develop a model for predicting MLA. Results Age, number of lesions, and diabetes mellitus correlated significantly with MLA of proximal or middle intermediate lesions. A regression model for predicting MLA （mm2） was derived from the data： 7.00 - 0.05 × （age） - 0.50 × （number of lesions）. A cut-off value of 3.1 mm2 was proposed for deciding when to perform percutaneous coronary intervention. Conclusion This model for predicting MLA of proximal or middle intermediate lesions in the LAD artery showed high accuracy, sensitivity, and specificity, indicating good diagnostic potential.展开更多
基金Supported by the National Natural Science Foundation of China (41101165)~~
文摘[Objective] This study aimed to explore the impact of climate change on wheat cropping by using province-specific historical data during 1996-2007. [Method] We established a panel data econometric model with lagged wheat cropping area and province-specific fixed-effects model to control the unobserved factors. [Result] The results showed that the temperature positively affects wheat cropping area, while precipitation does not have such impact. [Conclusion] The study provided empirical evidence for analysis of the determinants of wheat cropping area in China.
基金Supported by National Natural Science Foundation of China (No.70871087 and No.70931004)
文摘This paper investigates the scaled prediction variances in the errors-in-variables model and compares the performance with those in classic model of response surface designs for three factors.The ordinary least squares estimators of regression coefficients are derived from a second-order response surface model with errors in variables.Three performance criteria are proposed.The first is the difference between the empirical mean of maximum value of scaled prediction variance with errors and the maximum value of scaled prediction variance without errors.The second is the mean squared deviation from the mean of simulated maximum scaled prediction variance with errors.The last performance measure is the mean squared scaled prediction variance change with and without errors.In the simulations,1 000 random samples were performed following three factors with 20 experimental runs for central composite designs and 15 for Box-Behnken design.The independent variables are coded variables in these designs.Comparative results show that for the low level errors in variables,central composite face-centered design is optimal;otherwise,Box-Behnken design has a relatively better performance.
文摘Objective To identify clinical characteristics associated with the minimum lumen area （MLA） of proximal or middle intermediate lesions in the left anterior descending （LAD） artery, and to develop a model to predict MLA. Methods We retrospectively analyzed demographic data, medical history, and intravascular ultrasound findings for 90 patients with intermediate lesions in the LAD artery. Linear regression was used to identify factors affecting MLA, and multiple regression was used to develop a model for predicting MLA. Results Age, number of lesions, and diabetes mellitus correlated significantly with MLA of proximal or middle intermediate lesions. A regression model for predicting MLA （mm2） was derived from the data： 7.00 - 0.05 × （age） - 0.50 × （number of lesions）. A cut-off value of 3.1 mm2 was proposed for deciding when to perform percutaneous coronary intervention. Conclusion This model for predicting MLA of proximal or middle intermediate lesions in the LAD artery showed high accuracy, sensitivity, and specificity, indicating good diagnostic potential.
