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- W4377823170 abstract "Abstract The change of annual mean temperature generally has profound impact on our environment and decision-makers. Based on meterological data used for analysis in the past 63 years from 1951 to 2013, the weighted empirical likelihood for varying coefficient partially linear models with heteroscedastic errors is used to obtain the relationship between the index of the annual minimum climate temperature , the annual maximum climate temperature , the wind speed and annual climate temperature . Furthermore, we conclude that some meaningful characteristics for the relationship between the studied climate indices are obtained. Assisted by some statistical indexes of R 2 , we conclude that we get the goodness of the fit of the regression relationship based on the given data set with the method of weighted empirical likelihood for semi-parametric varying coefficient partially linear models with heteroscedastic error . At the same time, we have obtained that for the case of heteroscedastic data, the estimator of parametric with the empirical likelihood method with heteroscedastic data has the shorter confidence than the empirical likelihood method neglecting heteroscedastic factor." @default.
- W4377823170 created "2023-05-24" @default.
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- W4377823170 date "2023-05-23" @default.
- W4377823170 modified "2023-10-14" @default.
- W4377823170 title "Assessing the relationship between the annual average temperature and the indexes of annual average maximum , minimum temperature and wind speed in China based on the use of weighted empirical likelihood for semi-parametric varying coefficient partially linear models with heteroscedastic error" @default.
- W4377823170 doi "https://doi.org/10.21203/rs.3.rs-2891915/v1" @default.
- W4377823170 hasPublicationYear "2023" @default.
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