正态分布下多个方差转变点的检测与方法探讨
A Method of Detecting Multiple Change Point for Normal Distribution Process
DOI: 10.12677/AAM.2016.53040, PDF, HTML, XML, 下载: 2,179  浏览: 4,303  科研立项经费支持
作者: 沈卉卉:湖北经济学院,湖北 武汉;中国地质大学,湖北 武汉
关键词: 转变点贝叶斯方法极大似然方法先验分布似然密度函数Change Point Bayesian Method Maximum Likelihood Method Prior Distribution Likelihood Density Function
摘要: 经济系统数学模型中含有多个转变点的结构模型问题,本文对在均值相同情况下,方差多个转变点的检测方法采取的是将贝叶斯方法和极大似然方法结合起来,利用贝叶斯方法消去多余参数,极大似然方法可以回避转变点个数的先验分布信息未知的问题,给出有效的检测方法。
Abstract: The problem of structure model occurs multiple change points in the economic system of mathe-matical models. In this paper, we give the detection method for change point problems about the variance changes. We combine the Bayesian method with the maximum likelihood method on the detection about the variance multiple change points in the same mean. The elimination extra pa-rameters can make use of Bayesian method; the maximum likelihood method can avoid the un-known problems of the prior distribution information of the change points number. It is a practical method.
文章引用:沈卉卉. 正态分布下多个方差转变点的检测与方法探讨[J]. 应用数学进展, 2016, 5(3): 321-326. http://dx.doi.org/10.12677/AAM.2016.53040

参考文献

[1] Chen, J. and Gupta, A.K. (2000) Parametric Statistical Change Point Analysis. Birkhauser, Boston.
http://dx.doi.org/10.1007/978-1-4757-3131-6
[2] Inclan, C. (1993) Detection of Multiple Changes of Variance Using Posterior Odds. Journal of Business & Economic Statistics, 11, 289-300.
[3] 孙军, 姜诗意, 李宏纲. 经济序列变点的Bayes分析[J]. 统计研究, 2001(8): 27-30.
[4] Son, Y.S. and Kim, S.K. (2005) Bayesian Single Change Point Detection in a Sequence of Multivariate Normal Observations. Statistics, 39, 373-387.
http://dx.doi.org/10.1080/02331880500315339
[5] Chen, J., Yigiter, A. and Chang, K.C. (2011) A Bayesian Approach to Inference about a Change Point Model with Application to DNA Copy Number Expe-rimental Data. Journal of Applied Statistics, 38, 1899-1913.
http://dx.doi.org/10.1080/02664763.2010.529886
[6] Schwarz, G. (1978) Estimating the Dimension of a Model. Annals of Statistics, 6, 461-464.
http://dx.doi.org/10.1214/aos/1176344136
[7] Vostrikova, L.J.U. (1981) Detecting “Disorder” in Multidimensional Random Processes. Soviet Mathematics Doklady, 24, 55-59.
[8] 沈卉卉. 转变点判定及其在我国居民消费中的应用分析[J]. 商业时代, 2010 (3): 9-10.
[9] Jandhyala, V.K., Fotopoulos, S.B. and Hawkins, D.M. (2002) Detection and Estimation of Abrupt Changes in the Variability of a Process. Computational Statistics and Data Analysis, 40, 1-19.
http://dx.doi.org/10.1016/S0167-9473(01)00108-6
[10] Inclan, C. and Tiao, G.C. (1994) Use of Cumulative Sum of Squares for Retrospective Detection of Changes of Variances. Journal of American Statistcal Association, 89, 913-923.
[11] Shao, Y.E. and Lin, K.-S. (2015) Change Point Determination for an Attribute Process Using an Artificial Neural Network-Based Approach. Discrete Dynamics in Nature and Society, 2015, Article ID: 892740.
[12] Fotopoulos, S. and Jandhyala, V. (2001) Maximum Likelihood Estimation of a Change-Point for Exponentially Distributed Random Variables. Statistics & Probability Letters, 2001, 423-429.
http://dx.doi.org/10.1016/S0167-7152(00)00185-1
[13] Niaki, S.T.A. and Khedmati, M. (2014) Monotonic Change-Point Esti-mation of Multivariate Poisson Processes Using a Multi-Attribute Control Chart and MLE. International Journal of Production Re-search, 52, 2954-2982.
http://dx.doi.org/10.1080/00207543.2013.857797
[14] Pignatiello, J.J. and Samuel, T.R. (2001) Estimation of the Change Point of a Normal Process Mean in SPC Applications. Journal of Quality Technology, 33, 82-95.
[15] Shao, Y.E., Hou, C.D. and Wang, H.J. (2006) Estimation of the Change Point of a Gamma Process by Using the S Control Chart and MLE. Journal of the Chinese Institute of Industrial Engineers, 23, 207-214.
http://dx.doi.org/10.1080/10170660609509010
[16] Zhao, W.Z., Tian, Z. and Xia, Z.M. (2010) Ratio Test for Variance Change Point in Linear Process with Long Memory. Stat Papers, 51, 397-407.
http://dx.doi.org/10.1007/s00362-009-0202-3
[17] Monfared, M.E.D. and Lak, F. (2013) Bayesian Estimation of the Change Point Using Control Chart. Communications in Statistics—Theory and Methods, 42, 1572-1582.
http://dx.doi.org/10.1080/03610926.2011.594536
[18] Plummer, P.J. and Chen, J. (2014) A Bayesian Approach for Locating Change Points in a Compound Poisson Process with Application to Detecting DNA Copy Number Variations. Journal of Applied Statistics, 41, 423-438.
http://dx.doi.org/10.1080/02664763.2013.840272