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* 期刊論文

1.
Chien-Ming Chi, Ching-Kang Ing*, and Shu-Hui Yu (2021). Negative moment bounds for stochastic regression models with deterministic trends and their applications to prediction problems. Statistica Sinica,31: 2215-2237. SCI. 
2.
S. H. Yu and C. Y. Sin* (2021). On asymptotic risk of selecting models for possibly non-stationary time-series. Econometric Reviews, 40(4): 387-414. SSCI & SCI.
3.
C. Y. Sin and S. H. Yu (2019). Order selection for possibly infinite-order non-stationary time series. Advances in Statistical Analysis, 103: 187-216. SCI.
4.
Hsiang-Ling Hsu, Ching-Kang Ing, Tze Leung Lai and Shu-Hui Yu (2018). Multistage manufacturing processes: innovations in statistical modeling and inference.  In Proceedings of the Pacific Rim Statistical Conference for Production Engineering, 67-84. Springer.
5.
Ching-Kang Ing, Tze Leung Lai, Milan Shen, Ka Wai Tsang, and Shu-Hui Yu (2017). Multiple Testing in Regression Models with Applications to Fault Diagnosis in Big Data Era. Technometrics, 59(3): 351-360. SCI.
6.
Tzu-Chang F. Cheng, Ching-Kang Ing and Shu-Hui Yu (2015). Toward optimal model averaging in regression models with time series errors. Journal of Econometrics, 189(2): 321-334. SCI, SSCI.
7.
Tzu-Chang F. Cheng, Ching-Kang Ing and Shu-Hui Yu (2015). Inverse moment bounds for sample autocovariance matrices based on detrended time series and their applications. Linear Algebra and Its Applications, 473: 180-201. SCI.
8.
Shiou-Huei Huang, Chien-Ning Hsu, Shu-Hui Yu and Thau-Ming Cham (2012). Impact of drug pricing policy on utilization of and expenditure on angiotensin-converting enzyme inhibitors and angiotensin receptor blockers in Taiwan: a cross-sectional study. BMC Public Health, 12(288): 1471-2458. SCI.
9.
C.-K. Ing, C. Y. Sin and S. H. Yu (2012). Model selection for integrated autoregressive processes of infinite orde. Journal of Multivariate Analysis, 106: 57-71. SCI.
10.
S. H. Yu, C.-C. Lin and H.-W. Cheng (2012). A note on mean squared prediction error under the unit root model with deterministic trend. Journal of Time Series Analysis, 33: 276-286. SCI.
11.
S. H. Yu and S-C Liao (2012). Comparing a New Risk Measure with Some Traditional Risk Measures, Journal of Financial Review, 17: 1-19.
12.
C.-K. Ing, C. Y. Sin and S. H. Yu (2010). Prediction errors in nonstationary autoregression of infinite order. Econometric Theory, 26: 774-803. SCI, SSCI.
13.
C.-K. Ing, J.-L. Lin and S. H. Yu (2009). Toward optimal multistep forecasts in nonstationary autoregression. Bernoulli, 15: 402-437. SCI.
14.
俞淑惠 (2006). 銀行評價:整合財務績效及金融商品創新,市場競爭力之觀點,台灣管理學刊,第6卷第1期,頁35-58。(與郭憲章,溫德威,吳壽山合著)
15.
C.-K. Ing and Yu, S. H. (2003). On estimating conditional mean-squared prediction errors in autoregressive models. Journal of Time Series Analysis, 24: 401-422. SCI.

* 研討會論文

1.

俞淑惠, Mean squared prediction errors of integrated autoregressive models with polynomial time trends. The 11th ICSA International Conference, 2019.12.19-12/22, 中國杭州

2.

俞淑惠, On Asymptotic Risk of Selecting Models for Possibly Nonstationary Time-Series. The 5th International Conference on the Interface between Statistics and Engineering (ICISE2019), 2019.06.26-28, Korea

3.

俞淑惠, Higher Moments Modified VaR Estimators and Their Applications in Portfolio. 中國海洋大學金融系, 2018.7.6, 中國青島

4.

俞淑惠, Multiple Testing in Regression Models with Applications to Fault Diagnosis in Big Data Era. 2018 ICSA China Conference with the Focus on Data Science, 2018.07.02-05, 中國青島

5.

俞淑惠, On Asymptotic Risk of Order Selection in Integrated Autoregressive Models. 2018 ICSA Applied Statistics Symposium, 2018.06.14-17, New Jersey, USA

6.

俞淑惠, Multiple Testing in Regression Models with Applications to Fault Diagnosis in Big Data Era. 中國科學技術大學, 2018.1.23, 中國安徽

7.

Shu-Hui Yu (2017). Order selection for high-dimensional non-stationary time series. IFCS-2017. 201788-10, Tokyo, Japan

8.

Shu-Hui Yu (2017). Higher moments modified VaR estimators and their applications in portfolio. 2017 ICSA Applied Statistics Symposium. 2017625-28, Chicago, USA

9.

Shu-Hui Yu (2017). Higher moments modified VaR estimators and their applications in portfolio. 2017 統計學門研究成果發表會. 201727-8, 國立中興大學, 台中。

10.

Shu-Hui Yu (2016). Order selection for predictions in highdimensional AR model: the case of I(d) processes. International Symposium on Statistical Analysis for Large Complex Data. 20161121-23. University of Tsukuba, Japan.

11.

Shu-Hui Yu (2016). Estimating transition matrices: Applications to sovereign risk and exchange rate investment. Ibusuki International Seminar. 201636-8, Ibusuki, Japan.

12.

Shu-Hui Yu (2016). A VaR estimator under correlated defaults. Kumamoto International Symposium, 201633-5, Kumamoto University, Japan.

13.

Shu-Hui Yu (2016). Prediction errors in unit-root models. Waseda International Symposium. 2016229-32. Waseda University, Japan.

14.

Shu-Hui Yu (2015). Asymptotic inefficiency of BIC and asymptotic efficiency of TSIC: the case of an I(d) process. 2015831. Department of Applied Mathematics, Waseda University, Japan. 並於 2015 123-4日,在中央研究院發表、2016624-25日,在第二十五屆南區統計研討會暨105年度中華機率統計學會年會及學術研討會暨中華資料採礦協會年會及學術研討會(國立中山大學, 高雄)發表。

15.

Yu, S. H. (2015). Toward Optimal Model Averaging in Regression Models with Time Series Errors. Waseda Sympo. 201532-4, Waseda University, Japan.

16.

Yu, S. H. (2015). On Some New Modified Risk Measures and Implied Trading Strategies. Resort Seminar, 201535-7, Miura peninsula, Japan. 並於 2014 5月,於海峽兩岸研討會中發表。

17.

Ching-Kang Ing, Tze Leung Lai, Milan Shen, Hsiang-Ling Hsu, and Shu-Hui Yu (2014). Regression Models of Big Data for Root-Cause Identification and an Application to Semiconductors. Pacific Rim Statistics Conference on Production Engineering. 20141212-13, Shanghai, China.

18.

Yu, S. H. (2014). Toward Optimal Model Averaging in Regression Models with Time Series Errors. 2014年,中國統計學社社員大會暨國際統計學術研討會,國立交通大學,新竹。

19.

Yu, S. H. (2014). Apply Sparse Dynamic Factor Models to Arbitrage Pricing Theory. The 3rd Institute of Mathematical Statistics Asia Pacific Rim Meeting. 2014629日到73, Taipei, Taiwan.

20.

Ching-Kang Ing and Shu-Hui Yu (2014). Toward Optimal Model Averaging in Regression Models with Time Series Errors. The 10th International Symposium on Econometric Theory and Applications (SETA 2014). 2014529-30, Taipei, Taiwan.

21.

Yu, S. H. (2014). On Some New Modified Risk Measures and Implied Trading Strategies. 2014516-18日,第九屆海峽兩岸機率統計研討會,逢甲大學、國立中興大學,台中。

22.

俞淑惠 (2014) PM2.5監測儀器可靠度分析及其監測濃度之時間趨勢分析。2014年3月11-12日,2014年「能源利用與PM2.5污染控制」研習會,台灣大學,台北。

23.

俞淑惠 (2013) A Note On Mean Squared Prediction Error Under The Unit Root Model With Deterministic Trend. 2013年11月2日,2013年臺灣經濟計量學會年會,台灣大學,台北。

24.

Yu, S. H. (2012) A Note On Mean Squared Prediction Error Under The Unit Root Model With Deterministic Trend. 2012 Joint Statistical Meetings. 2012年7月28日-8月2日, San Diego, California, USA.

25.

俞淑惠 (2012) A Study on Value-at-Risk of Basel III. 2012年6月29-30日, 第二十一屆南區統計研討會, 輔仁大學. Invited speaker.

26.

Yu, S. H. (2011) A Note On Mean Squared Prediction Error Under The Unit Root Model With Deterministic Trend. Joint Meeting of the 2011 Taipei International Statistical Symposium and 7th Conference of the Asian Regional Section of the IASC. 2011 年12月16-19日, Statistical Sinica, Taipei. Invited Speaker.

27.

Yu, S. H. (2011) Model Selection for Integrated Autoregressive Processes of Infinite Order. 2011年6月24-25日, 第二十屆南區統計研討會, 國立中正大學. Invited speaker.

28.

Yu, S. H. (2010) Time-Varying Logistic Regression Models for Predicting Corporate Distress. 2010年7月6-7日, 第十九屆南區統計研討會, 國立成功大學. Invited speaker.

29.

Yu, S. H. (2009) Estimating credit transition matrices using two different data types by matrix autoregressive models. Conference on Statistical Models and Methods in Quantitative Finance and Related Topics 2009. Statistical Sinica, Taipei. Invited Speaker.

30.

Yu, S. H. (2008) Estimating Credit Transition Matrices Using Matrix Autoregressive Models. International Conference on Mathematics of Finance and Related Application. The University of Hong Kong, Hong Kong.

31.

Yu, S. H. (2005). A New Value at Risk Calculation in Instability Markets Subject to Volatility Clustering Phenomenon. 2005 NBER Conference.NBER/NSF/CFS satellite workshop on ‘Financial Risk and Time Series Analysis’, Germany.

32.

Yu, S. H. (2005).Time-Varying Dynamic Models for Predicting Corporate Distress. 2005 Joint Statistical Meeting, Minneapolis, U.S.A.

33.

Yu, S. H. (2003). Model Selection for Logistic Regression Model with Mixed Type Explanatory Variables. Bernoulli Society East Asian and Pacific Regional (EAPR) Conference 2003, Hong Kong.


 
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更新日期:2024/3/18 下午 03:54:17

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