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題名 非線性時間數列模糊轉捩區間之確認
Fuzzy change period identification for the nonlinear time series
作者 李玉如
Lee, Alice
貢獻者 吳柏林
Wu, Berllin
李玉如
Lee, Alice
關鍵詞 結構性改變
轉捩點
模糊時間數列
□ 水準
模糊點
模糊轉捩區間
模糊分類
歸屬度
模糊度
Structural change
change point
fuzzy time series
□level
FCP
日期 1994
1993
上傳時間 29-Apr-2016 15:30:48 (UTC+8)
摘要 對於一個具有結構性改變性質的非線性時間數列，通常很難判斷何處為轉
As far as structural change of a non-linear time series is
參考文獻 Bagshaw, M. and Johnson, R. A. (1977). Sequential procedures for detecting parameter changes in a time series model. Journal of American statistic Association, 72, 593-597.
Balke, N. S. (1993). Detecting level shifts in time series. Journal of Business and Economic Statistics, 11(1), 81-92.
Barry, D. and Hartigan, J. A. (1993). A bayesian analysis for change point problems. Journal of the American Statistical Association, 88(421), 309-319.
Bezdek, J. C. (1981). Pattern Recognition with Fuzzy Objective Function Algorithms. New York: Ploenum Press.
Broemeling, L.D. and Tsurumi, H. (1987). Econometrics and Structural change, Marcel Dekker Inc.
Chan, W. S. and Tong, H. (1986). On test for non-linearity in time series analysis. Journal of Forecasting, 5, 217-228.
Cutsem, B. V. and Gath, I, (1993). Detection of outliers and robust estimation using fuzzy clustering. Computational Statistics and Data Analysis, 15, 47-61.
Gardner, E. S. (1983). Automatic monitoring of forecast errors. Journal of Forecasting, 2, 1-21.
Gooijer, J. G. D. and Kumar, K.(1992). Some recent developments in non-linear time series modeling, testing, and forecasting. International Journal of Forecasting, 8,
135-156.
Hathaway, R. J. and Bezdek, J. C. (1993) Switching regression models and fuzzy clustering. IEEE Transactions on fuzzy systems, 1(3), 195-204.
Heshmaty, B. and Kandel, A. (1985). Fuzzy linear regression and its applications to forecasting in uncertain environment. Fuzzy Sets and Systems, 15, 159-191.
Li, W. K. (1990). A simple one degree of freedom test for non-linear time series model discrimination. Working paper (Department of Statistics, University of Hong Kong.)
Oh, S. B., Kim, W. and Lee, J. K. (1990), An approach to causal modeling in fuzzy environment and its application. Fuzzy Sets and Systems, 35, 43-55.
Page, E. S. (1955). A test for change in a parameter occurring at an unknown point. Biometrika, 42, 523-527.
Priestley, M, B. (1988). Non-linear and non-stationary time series analysis. Academic Press inc.
Sastri, T., Flores, B. and Valdes, J. (1989). Detecting points of change in time series. Computers Opns Res., 16(3), 271-293.
Song, Q. and Chissom, B. S. (1993 a). Fuzzy time series and its models. Fuzzy Sets and Systems, 54, 269-277.
Song, Q. and Chissom, B. S. (1993 b). Forecasting enrollments with fuzzy time series – part I. Fuzzy Sets and Systems, 54, 1-9.
Tong, H. (1990). Non-linear time series. A dynamical system approach. Oxford University Press, New York.
Tong, H. and Yeung, I. (1991). On tests for self-exciting threshold autoregressive-type Non-linearity in partially observed time series. Appl. Statist, 40(1), 43-62.
Tsay, R. S. (1988). Outliers, level shifts, and variance changes in time series. Journal of forecasting, 7, 1-20.
Wu, B. and Shih, N., (1992). On the identification problem for bilinear time series models. J. Statist. Comput. Simul. 43, 129-161.
Wu, B. (1994). Identification environment and robust forecasting for nonlinear time series. Computational Economics, 7, 37-53.
Yoshinari, Y. Pedrycz, W. and Hirota, K. (1993). Construction of fuzzy models through clustering techniques. Fuzzy sets and systems, 54, 157-165.
Zadeh, L. A. (1965). Fuzzy sets. Inform. And Control, 8, 338-353.
描述 碩士
國立政治大學
統計學系
81354005
資料來源 http://thesis.lib.nccu.edu.tw/record/#B2002003820
資料類型 thesis
dc.contributor.advisor 吳柏林zh_TW
dc.contributor.advisor Wu, Berllinen_US
dc.contributor.author (Authors) 李玉如zh_TW
dc.contributor.author (Authors) Lee, Aliceen_US
dc.creator (作者) 李玉如zh_TW
dc.creator (作者) Lee, Aliceen_US
dc.date (日期) 1994en_US
dc.date (日期) 1993en_US
dc.date.accessioned 29-Apr-2016 15:30:48 (UTC+8)-
dc.date.available 29-Apr-2016 15:30:48 (UTC+8)-
dc.date.issued (上傳時間) 29-Apr-2016 15:30:48 (UTC+8)-
dc.identifier (Other Identifiers) B2002003820en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/88352-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 統計學系zh_TW
dc.description (描述) 81354005zh_TW
dc.description.abstract (摘要) 對於一個具有結構性改變性質的非線性時間數列，通常很難判斷何處為轉zh_TW
dc.description.abstract (摘要) As far as structural change of a non-linear time series isen_US
dc.description.tableofcontents 1、 Introduction………………………………………………………………………………………………………1
2、 Change point detecting method…………………………………………………………………………………………………………….…5
2.1 Preliminary result…………………………………………………………………………………………………………..………5
2.2 Concept of fuzzy change period…………………………………………………………………………………………………..…….………9
3、 Change period by fuzzy detecting…………………………………………………………………………………….……………………..……11
3.1 Fuzzy clustering on time series………………………………………………….………..……12
3.2 Fuzzy point and Fuzzy change period…………………………………………….......……14
3.3 Some properties on Fuzzy time series……………………………………..………….……17
3.4 Deteching α-level of Fuzzy change period………………………………………………18
4、 Application to the time series of Taiwan birth rate……….………………….…………..…30
5、 Conclusion……………………………………………………………………………….………………………35
6、 Reference……………………………………………………………………………………….….……………36		zh_TW
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#B2002003820en_US
dc.subject (關鍵詞) 結構性改變zh_TW
dc.subject (關鍵詞) 轉捩點zh_TW
dc.subject (關鍵詞) 模糊時間數列zh_TW
dc.subject (關鍵詞) □ 水準zh_TW
dc.subject (關鍵詞) 模糊點zh_TW
dc.subject (關鍵詞) 模糊轉捩區間zh_TW
dc.subject (關鍵詞) 模糊分類zh_TW
dc.subject (關鍵詞) 歸屬度zh_TW
dc.subject (關鍵詞) 模糊度zh_TW
dc.subject (關鍵詞) Structural changeen_US
dc.subject (關鍵詞) change pointen_US
dc.subject (關鍵詞) fuzzy time seriesen_US
dc.subject (關鍵詞) □levelen_US
dc.subject (關鍵詞) FCPen_US
dc.title (題名) 非線性時間數列模糊轉捩區間之確認zh_TW
dc.title (題名) Fuzzy change period identification for the nonlinear time seriesen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) Bagshaw, M. and Johnson, R. A. (1977). Sequential procedures for detecting parameter changes in a time series model. Journal of American statistic Association, 72, 593-597.
Balke, N. S. (1993). Detecting level shifts in time series. Journal of Business and Economic Statistics, 11(1), 81-92.
Barry, D. and Hartigan, J. A. (1993). A bayesian analysis for change point problems. Journal of the American Statistical Association, 88(421), 309-319.
Bezdek, J. C. (1981). Pattern Recognition with Fuzzy Objective Function Algorithms. New York: Ploenum Press.
Broemeling, L.D. and Tsurumi, H. (1987). Econometrics and Structural change, Marcel Dekker Inc.
Chan, W. S. and Tong, H. (1986). On test for non-linearity in time series analysis. Journal of Forecasting, 5, 217-228.
Cutsem, B. V. and Gath, I, (1993). Detection of outliers and robust estimation using fuzzy clustering. Computational Statistics and Data Analysis, 15, 47-61.
Gardner, E. S. (1983). Automatic monitoring of forecast errors. Journal of Forecasting, 2, 1-21.
Gooijer, J. G. D. and Kumar, K.(1992). Some recent developments in non-linear time series modeling, testing, and forecasting. International Journal of Forecasting, 8,
135-156.
Hathaway, R. J. and Bezdek, J. C. (1993) Switching regression models and fuzzy clustering. IEEE Transactions on fuzzy systems, 1(3), 195-204.
Heshmaty, B. and Kandel, A. (1985). Fuzzy linear regression and its applications to forecasting in uncertain environment. Fuzzy Sets and Systems, 15, 159-191.
Li, W. K. (1990). A simple one degree of freedom test for non-linear time series model discrimination. Working paper (Department of Statistics, University of Hong Kong.)
Oh, S. B., Kim, W. and Lee, J. K. (1990), An approach to causal modeling in fuzzy environment and its application. Fuzzy Sets and Systems, 35, 43-55.
Page, E. S. (1955). A test for change in a parameter occurring at an unknown point. Biometrika, 42, 523-527.
Priestley, M, B. (1988). Non-linear and non-stationary time series analysis. Academic Press inc.
Sastri, T., Flores, B. and Valdes, J. (1989). Detecting points of change in time series. Computers Opns Res., 16(3), 271-293.
Song, Q. and Chissom, B. S. (1993 a). Fuzzy time series and its models. Fuzzy Sets and Systems, 54, 269-277.
Song, Q. and Chissom, B. S. (1993 b). Forecasting enrollments with fuzzy time series – part I. Fuzzy Sets and Systems, 54, 1-9.
Tong, H. (1990). Non-linear time series. A dynamical system approach. Oxford University Press, New York.
Tong, H. and Yeung, I. (1991). On tests for self-exciting threshold autoregressive-type Non-linearity in partially observed time series. Appl. Statist, 40(1), 43-62.
Tsay, R. S. (1988). Outliers, level shifts, and variance changes in time series. Journal of forecasting, 7, 1-20.
Wu, B. and Shih, N., (1992). On the identification problem for bilinear time series models. J. Statist. Comput. Simul. 43, 129-161.
Wu, B. (1994). Identification environment and robust forecasting for nonlinear time series. Computational Economics, 7, 37-53.
Yoshinari, Y. Pedrycz, W. and Hirota, K. (1993). Construction of fuzzy models through clustering techniques. Fuzzy sets and systems, 54, 157-165.
Zadeh, L. A. (1965). Fuzzy sets. Inform. And Control, 8, 338-353.		zh_TW