Evaluation of human bioclimates using quantile regression: A China case study

Pin T. Ng; Yuk Yee Yan

doi:10.2747/0272-3646.29.5.387

Evaluation of human bioclimates using quantile regression: A China case study

Pin T. Ng, Yuk Yee Yan^*

^*Corresponding author for this work

Research output: Contribution to journal › Journal article › peer-review

1 Citation (Scopus)

Abstract

A nonparametric version of quantile regressions was applied to investigate the human bioclimates in China through the use of the CLO (clothing requirements) index. Quantile regression surface maps produced from the whole spectrum of the CLO distribution provided better insights into the spatial characteristics of clothing requirements and information on the spread and variations of the distribution. Univariate quantile regression curves were constructed to display the temporal variability of CLO at different locations. Hence, this analysis produced a more complete picture of the human bioclimates of the various regions in China.

Original language	English
Pages (from-to)	387-403
Number of pages	17
Journal	Physical Geography
Volume	29
Issue number	5
DOIs	https://doi.org/10.2747/0272-3646.29.5.387
Publication status	Published - 2008

Scopus Subject Areas

Environmental Science(all)
Atmospheric Science
Earth and Planetary Sciences (miscellaneous)
Earth and Planetary Sciences(all)

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abstract = "A nonparametric version of quantile regressions was applied to investigate the human bioclimates in China through the use of the CLO (clothing requirements) index. Quantile regression surface maps produced from the whole spectrum of the CLO distribution provided better insights into the spatial characteristics of clothing requirements and information on the spread and variations of the distribution. Univariate quantile regression curves were constructed to display the temporal variability of CLO at different locations. Hence, this analysis produced a more complete picture of the human bioclimates of the various regions in China.",

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AB - A nonparametric version of quantile regressions was applied to investigate the human bioclimates in China through the use of the CLO (clothing requirements) index. Quantile regression surface maps produced from the whole spectrum of the CLO distribution provided better insights into the spatial characteristics of clothing requirements and information on the spread and variations of the distribution. Univariate quantile regression curves were constructed to display the temporal variability of CLO at different locations. Hence, this analysis produced a more complete picture of the human bioclimates of the various regions in China.

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Evaluation of human bioclimates using quantile regression: A China case study

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