The study discusses accuracy evaluation methods for offshore wind energy resources by using scatterometer SeaWinds-derived wind speed and Weibull parameters. The purpose of this study is to evaluate accuracies of SeaW...The study discusses accuracy evaluation methods for offshore wind energy resources by using scatterometer SeaWinds-derived wind speed and Weibull parameters. The purpose of this study is to evaluate accuracies of SeaWinds-derived Weibull mean wind speed and energy density by considering uncertainties inherent in SeaWinds wind speed estimates. In this study, 1159 SeaWinds-derived wind speeds covering the KEO buoy are used for estimating two Weibull parameters, scale and shape. On the other hand, observed wind speeds from 2004 to 2008 at the KEO buoy are used for simulating three kinds of wind speeds in order to quantify some uncertainties inherent in SeaWinds-derived wind speeds. It is found that uncertainties associated with wind speed estimates （operational wind speed range, sampling time） show small differences in scale, shape and Weibull mean wind speed except energy density among the simulated datasets. Furthermore, the upper and lower bounds of 90% confidence interval corresponding to SeaWinds number of observations indicate 4-2.5% error of Weibull mean wind speed and 4-6.8% error of energy density, respectively.展开更多
In this article, we propose a novel, multilevel, dynamic factor model, to determine endogenously clustered regions for the investigation of regional clustering and synchronization of provincial business fluctuations i...In this article, we propose a novel, multilevel, dynamic factor model, to determine endogenously clustered regions for the investigation of regional clustering and synchronization of provincial business fluctuations in China. The parameter identification and model estimation was conducted using the Markov Chain Monte Carlo method. We then conducted an empirical study of the provincial business fluctuations in China(31 Chinese provinces are considered except Hong Kong, Macao, and Taiwan due to the data unavailability), which were sampled from January 2000 to December 2015. Our results indicated that these provinces could be clustered into four regions: leading, coincident, lagging, and overshooting. In comparison with traditional geographical divisions, this novel clustering into four regions enabled the regional business cycle synchronization to be more accurately captured. Within the four regional clusters it was possible to identify substantial heterogeneities among regional business cycle fluctuations, especially during the periods of the 2008 financial crisis and the ‘four-trillion economic stimulus plan'.展开更多
The Contingent Valuation Method is used to evaluate individual preferences for a change concerning a public non-market resource or property. The objective is to build a nonparametric forecasting model of an individual...The Contingent Valuation Method is used to evaluate individual preferences for a change concerning a public non-market resource or property. The objective is to build a nonparametric forecasting model of an individual＇s Willingness To Pay according to geographical location. Within this framework, an estimator （of type Nadaraya-Watson） is proposed for the regression of the variable related to geolocation. The specific characteristics of the location variable lead us to a more general regression model than the traditional models. Results are established for convergence of our estimator.展开更多
文摘The study discusses accuracy evaluation methods for offshore wind energy resources by using scatterometer SeaWinds-derived wind speed and Weibull parameters. The purpose of this study is to evaluate accuracies of SeaWinds-derived Weibull mean wind speed and energy density by considering uncertainties inherent in SeaWinds wind speed estimates. In this study, 1159 SeaWinds-derived wind speeds covering the KEO buoy are used for estimating two Weibull parameters, scale and shape. On the other hand, observed wind speeds from 2004 to 2008 at the KEO buoy are used for simulating three kinds of wind speeds in order to quantify some uncertainties inherent in SeaWinds-derived wind speeds. It is found that uncertainties associated with wind speed estimates （operational wind speed range, sampling time） show small differences in scale, shape and Weibull mean wind speed except energy density among the simulated datasets. Furthermore, the upper and lower bounds of 90% confidence interval corresponding to SeaWinds number of observations indicate 4-2.5% error of Weibull mean wind speed and 4-6.8% error of energy density, respectively.
基金Under the auspices of the National Natural Science Foundation of China(No.71371160)the Program for Changjiang Youth Scholars(No.Q2016131)the Program for New Century Excellent Talents in University(No.NCET-13-0509)
文摘In this article, we propose a novel, multilevel, dynamic factor model, to determine endogenously clustered regions for the investigation of regional clustering and synchronization of provincial business fluctuations in China. The parameter identification and model estimation was conducted using the Markov Chain Monte Carlo method. We then conducted an empirical study of the provincial business fluctuations in China(31 Chinese provinces are considered except Hong Kong, Macao, and Taiwan due to the data unavailability), which were sampled from January 2000 to December 2015. Our results indicated that these provinces could be clustered into four regions: leading, coincident, lagging, and overshooting. In comparison with traditional geographical divisions, this novel clustering into four regions enabled the regional business cycle synchronization to be more accurately captured. Within the four regional clusters it was possible to identify substantial heterogeneities among regional business cycle fluctuations, especially during the periods of the 2008 financial crisis and the ‘four-trillion economic stimulus plan'.
文摘The Contingent Valuation Method is used to evaluate individual preferences for a change concerning a public non-market resource or property. The objective is to build a nonparametric forecasting model of an individual＇s Willingness To Pay according to geographical location. Within this framework, an estimator （of type Nadaraya-Watson） is proposed for the regression of the variable related to geolocation. The specific characteristics of the location variable lead us to a more general regression model than the traditional models. Results are established for convergence of our estimator.
