The thermal decomposition temperature is one of the most important parameters to evaluate fire hazard of organic peroxide. A quantitative structure-property relationship model was proposed for estimating the thermal d...The thermal decomposition temperature is one of the most important parameters to evaluate fire hazard of organic peroxide. A quantitative structure-property relationship model was proposed for estimating the thermal decomposition temperatures of organic peroxides. The entire set of 38 organic peroxides was at random divided into a training set for model development and a prediction set for external model validation. The novel local molecular descriptors of AT1, AT2, AT3, AT4, AT5, AT6 and global molecular descriptor of ATC have been proposed in order to character organic peroxides’ molecular structures. An accurate quantitative structure-property relationship （QSPR） equation is developed for the thermal decomposition temperatures of organic peroxides. The statistical results showed that the QSPR model was obtained using the multiple linear regression （MLR） method with correlation coefficient （R）, standard deviation （S）, leave-one-out validation correlation coefficient （RCV） values of 0.9795, 6.5676 ℃ and 0.9328, respectively. The average absolute relative deviation （AARD） is only 3.86% for the experimental values. Model test by internal leave-one-out cross validation and external validation and molecular descriptor interpretation were discussed. Comparison with literature results demonstrated that novel local and global descriptors were useful molecular descriptors for predicting the thermal decomposition temperatures of organic peroxides.展开更多
In this paper, the authors analyze the adequacy of GARCH-type models to analyze oil price behavior by applying two types of non-parametric tests, the Hinich portmanteau test for non-linear dependence and a frequency-d...In this paper, the authors analyze the adequacy of GARCH-type models to analyze oil price behavior by applying two types of non-parametric tests, the Hinich portmanteau test for non-linear dependence and a frequency-dominant test of time reversibility, the reverse test based on the bispectrum, to explore the high-order spectrum properties of the Mexican oil price series. The results suggest strong evidence of a non-linear structure and time irreversibility. Therefore, it does not comply with the i.i.d （independent and identically distributed） property. The non-linear dependence, however, is not consistent throughout the sample period, as indicated by a windowed test, suggesting episodic nonlinear dependence. The results imply that GARCH models cannot capture the series structure.展开更多
This study is to use cointegration, linear and non-linear Granger causality test to investigate the relationship between carbon dioxide （CO2） emissionand economic growth （GDP） in China for the period 1961-2010. Ou...This study is to use cointegration, linear and non-linear Granger causality test to investigate the relationship between carbon dioxide （CO2） emissionand economic growth （GDP） in China for the period 1961-2010. Our analysis shows that CO2 emission and GDP are balanced in the long-run. The results suggest that there is evidence that economic development can improve environmental degradation in the long-run. Moreover, the result of linear and non-linear Granger causality test indicates a long-run unidirectional causality running from GDP to CO2 emissions. The study suggests that in the long run, economic growth may have an adverse effect on the CO2 emissions in China. Government should take into account the environment in their current policies, which may be of great importance for policy decision-makers to develop economic policies to preserve economic growth while curbing of carbon emissions.展开更多
The purpose of this paper is to test the underlying serial correlation in a partially linear single-index model. Under mild conditions, the proposed test statistics are shown to have standard chi- squared distribution...The purpose of this paper is to test the underlying serial correlation in a partially linear single-index model. Under mild conditions, the proposed test statistics are shown to have standard chi- squared distribution asymptotically when there is no serial correlation in the error terms. To illustrate their finite sample properties, simulation experiments, as well as a real data example, are also provided. It is revealed that the finite sample performances of the proposed test statistics are satisfactory in terms of both estimated sizes and powers.展开更多
基金Project(2015SK20823) supported by Science and Technology Project of Hunan Province,ChinaProject(15A001) supported by Scientific Research Fund of Hunan Provincial Education Department,China+2 种基金Project(2017CL06) supported by Hunan Provincial Key Laboratory of Materials Protection for Electric Power and Transportation,ChinaProject(k1403029-11) supported by Science and Technology Project of Changsha City,ChinaProject(CX2015B372) supported by the Hunan Provincial Innovation Foundation for Postgraduate,China
文摘The thermal decomposition temperature is one of the most important parameters to evaluate fire hazard of organic peroxide. A quantitative structure-property relationship model was proposed for estimating the thermal decomposition temperatures of organic peroxides. The entire set of 38 organic peroxides was at random divided into a training set for model development and a prediction set for external model validation. The novel local molecular descriptors of AT1, AT2, AT3, AT4, AT5, AT6 and global molecular descriptor of ATC have been proposed in order to character organic peroxides’ molecular structures. An accurate quantitative structure-property relationship （QSPR） equation is developed for the thermal decomposition temperatures of organic peroxides. The statistical results showed that the QSPR model was obtained using the multiple linear regression （MLR） method with correlation coefficient （R）, standard deviation （S）, leave-one-out validation correlation coefficient （RCV） values of 0.9795, 6.5676 ℃ and 0.9328, respectively. The average absolute relative deviation （AARD） is only 3.86% for the experimental values. Model test by internal leave-one-out cross validation and external validation and molecular descriptor interpretation were discussed. Comparison with literature results demonstrated that novel local and global descriptors were useful molecular descriptors for predicting the thermal decomposition temperatures of organic peroxides.
文摘In this paper, the authors analyze the adequacy of GARCH-type models to analyze oil price behavior by applying two types of non-parametric tests, the Hinich portmanteau test for non-linear dependence and a frequency-dominant test of time reversibility, the reverse test based on the bispectrum, to explore the high-order spectrum properties of the Mexican oil price series. The results suggest strong evidence of a non-linear structure and time irreversibility. Therefore, it does not comply with the i.i.d （independent and identically distributed） property. The non-linear dependence, however, is not consistent throughout the sample period, as indicated by a windowed test, suggesting episodic nonlinear dependence. The results imply that GARCH models cannot capture the series structure.
基金supported by National Natural Science Foundation of China(71161011)
文摘This study is to use cointegration, linear and non-linear Granger causality test to investigate the relationship between carbon dioxide （CO2） emissionand economic growth （GDP） in China for the period 1961-2010. Our analysis shows that CO2 emission and GDP are balanced in the long-run. The results suggest that there is evidence that economic development can improve environmental degradation in the long-run. Moreover, the result of linear and non-linear Granger causality test indicates a long-run unidirectional causality running from GDP to CO2 emissions. The study suggests that in the long run, economic growth may have an adverse effect on the CO2 emissions in China. Government should take into account the environment in their current policies, which may be of great importance for policy decision-makers to develop economic policies to preserve economic growth while curbing of carbon emissions.
基金supported by CCNU under Grant No.09A01002the SCR of Chongqing Municipal Education Commission under Grant No.KJ110713the National Natural Science Foundation of China under Grant Nos.11101452 and 71172093
文摘The purpose of this paper is to test the underlying serial correlation in a partially linear single-index model. Under mild conditions, the proposed test statistics are shown to have standard chi- squared distribution asymptotically when there is no serial correlation in the error terms. To illustrate their finite sample properties, simulation experiments, as well as a real data example, are also provided. It is revealed that the finite sample performances of the proposed test statistics are satisfactory in terms of both estimated sizes and powers.
