"University of Manchester Institute of Science and Technology"@en . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . "12220"^^ . . . . . . . . . . . . . "Tsinghua University, China"@en . . . . "Howell Tong"@en . . "Howell Tong (simplified Chinese: \u6C64\u5BB6\u8C6A; traditional Chinese: \u6E6F\u5BB6\u8C6A; pinyin: T\u0101ng Ji\u0101h\u00E1o; born in 1944 in Hong Kong) is a statistician who has made fundamental contributions to analysis, semi-parametric statistics, non-parametric statistics, dimension reduction, model selection, likelihood-free statistics and other areas. In the words of Professor Peter Whittle (FRS), \u2018The striking feature of Howell Tong\u2019s \u2026 is thecontinuing freshness, boldness and spirit of enquiry which inform them-indeed, proper qualities foran explorer. He stands as the recognised innovator and authority in his subject, while remainingdisarmingly direct and enthusiastic .\u2019\u00B9 And his work, in the words of Sir David Cox, \u2018links two fascinating fields, nonlinear time series and deterministic dynamical systems.\u2019\u00B2 He is the father of the threshold time series models, which have extensive applications in ecology, economics, epidemiology and finance. (See external links for detail.) Besides nonlinear time series analysis, he was the co-author of a seminal paper, which he read to the Royal Statistical Society, on dimension reduction in semi-parametric statistics by pioneering the approach based on minimum average variance estimation. He has also made numerous novel contributions to nonparametric statistics (obtaining the surprising result that cross-validation does not suffer from the curse of dimensionality for consistent estimation of the embedding dimension of a dynamical system), Markov chain modelling (with application to weather data), reliability, non-stationary time series analysis (in both the frequency domain and the time domain) and wavelets."@en . . . . . . . "22304790"^^ . . . . . . . . . . . . "University of Hong Kong"@en . . . . "London School of Economics"@en . . . "\u0647\u0648\u064A\u0644 \u062A\u0648\u0646\u063A (\u0628\u0627\u0644\u0625\u0646\u062C\u0644\u064A\u0632\u064A\u0629: Howell Tong)\u200F \u0647\u0648 \u0625\u062D\u0635\u0627\u0626\u064A \u0628\u0631\u064A\u0637\u0627\u0646\u064A\u060C \u0648\u0644\u062F \u0641\u064A 1944 \u0641\u064A \u0647\u0648\u0646\u063A \u0643\u0648\u0646\u063A \u0641\u064A \u0627\u0644\u0635\u064A\u0646."@ar . . "\u6E6F\u5BB6\u8C6A"@en . . . . . . . . . . "Hongzhi An; Kung-Sik Chan; Rong Chen; Bing Cheng; Jan DeGooijer; Cees Diks; Barbel Finkenstaedt; Simone Giannerini; Dong Li; Wai Keung Li; Shiqing Ling; Manfred Mudelsee; Ken Siu; Ruey Tsay; Yingcun Xia; Qiwei Yao"@en . . "\u0647\u0648\u064A\u0644 \u062A\u0648\u0646\u063A"@ar . . . . . . . . . . . . "\u0647\u0648\u064A\u0644 \u062A\u0648\u0646\u063A (\u0628\u0627\u0644\u0625\u0646\u062C\u0644\u064A\u0632\u064A\u0629: Howell Tong)\u200F \u0647\u0648 \u0625\u062D\u0635\u0627\u0626\u064A \u0628\u0631\u064A\u0637\u0627\u0646\u064A\u060C \u0648\u0644\u062F \u0641\u064A 1944 \u0641\u064A \u0647\u0648\u0646\u063A \u0643\u0648\u0646\u063A \u0641\u064A \u0627\u0644\u0635\u064A\u0646."@ar . . . . . "\u6C64\u5BB6\u8C6A"@en . . . . . . . "\u6E6F\u5BB6\u8C6A"@en . . . . . . . . . . . . "University of Kent"@en . . . . . "Howell Tong (simplified Chinese: \u6C64\u5BB6\u8C6A; traditional Chinese: \u6E6F\u5BB6\u8C6A; pinyin: T\u0101ng Ji\u0101h\u00E1o; born in 1944 in Hong Kong) is a statistician who has made fundamental contributions to analysis, semi-parametric statistics, non-parametric statistics, dimension reduction, model selection, likelihood-free statistics and other areas. In the words of Professor Peter Whittle (FRS), \u2018The striking feature of Howell Tong\u2019s \u2026 is thecontinuing freshness, boldness and spirit of enquiry which inform them-indeed, proper qualities foran explorer. He stands as the recognised innovator and authority in his subject, while remainingdisarmingly direct and enthusiastic .\u2019\u00B9 And his work, in the words of Sir David Cox, \u2018links two fascinating fields, nonlinear time series and deterministic dynamical systems.\u2019\u00B2 He is the fath"@en . . . . . . . . . "Chinese University of Hong Kong"@en . . . . . "\u6E6F\u5BB6\u8C6A"@en . . . . . "Distinguished Achievement Award, International Chinese Statistical Association"@en . . . . "Academy of Mathematics and System Sciences, the Chinese Academy of Sciences"@en . . . . . . . . . . . . . . . . . "1120335046"^^ . . . . "State Prize Class 2 for Natural Sciences, China"@en . . . "Guy Medal in Silver, Royal Statistical Society, U.K."@en . . . . . . . "University of Electronic Science and Technology of China, China"@en . . . "Howell Tong"@en . . "T\u0101ng Ji\u0101h\u00E1o"@en . . . "Howell Tong"@en . . "Honorary Fellow of the Institute and Faulty of Actuaries, U.K."@en . . . . .