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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Power law process models for nonhomogeneous poisson process change-points /

Richardson, Mary Golden, January 1997 (has links)
Thesis (Ph. D.)--University of Missouri-Columbia, 1997. / Typescript. Vita. Includes bibliographical references (leaves 253-257). Also available on the Internet.
2

Power law process models for nonhomogeneous poisson process change-points

Richardson, Mary Golden, January 1997 (has links)
Thesis (Ph. D.)--University of Missouri-Columbia, 1997. / Typescript. Vita. Includes bibliographical references (leaves 253-257). Also available on the Internet.
3

Exact test for an epidemic change in a sequence of exponentially distributed random variables.

January 2005 (has links)
Lai Kim Fung. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2005. / Includes bibliographical references (leaves 55-57). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Likelihood Ratio Test Statistic --- p.6 / Chapter 2.1 --- Introduction --- p.6 / Chapter 2.2 --- Formulation --- p.6 / Chapter 2.3 --- Likelihood Ratio Type Statistic --- p.7 / Chapter 2.4 --- Dirichlet Distribution --- p.8 / Chapter 2.5 --- Edgeworth Expansion --- p.12 / Chapter 3 --- Divided Difference --- p.15 / Chapter 3.1 --- Introduction --- p.15 / Chapter 3.2 --- Definition of Divided Difference --- p.15 / Chapter 3.3 --- Theorem --- p.17 / Chapter 3.4 --- Proof of the Theorem --- p.18 / Chapter 3.5 --- Application of Theorem --- p.19 / Chapter 4 --- Computational Results --- p.22 / Chapter 4.1 --- Introduction --- p.22 / Chapter 4.2 --- Critical Values for Moderate and Large Sample Sizes --- p.22 / Chapter 4.3 --- Critical Values for Small Sample Sizes --- p.23 / Chapter 4.3.1 --- Exact Critical Values --- p.23 / Chapter 4.3.2 --- Edgeworth Expansion Results --- p.23 / Chapter 4.3.3 --- Simulation Results --- p.23 / Chapter 4.4 --- Power --- p.24 / Chapter 5 --- Illustrative Examples --- p.29 / Chapter 5.1 --- Stanford Heart Transplant Data --- p.29 / Chapter 5.1.1 --- The Data --- p.29 / Chapter 5.1.2 --- Result --- p.31 / Chapter 5.2 --- Air Conditioning Data --- p.31 / Chapter 5.2.1 --- The Data --- p.31 / Chapter 5.2.2 --- Result --- p.32 / Chapter 5.3 --- Insulating Fluid Failure Data --- p.33 / Chapter 5.3.1 --- The Data --- p.33 / Chapter 5.3.2 --- Result --- p.33 / Chapter 6 --- Conclusion and Further Research Topic --- p.35 / Chapter 6.1 --- Conclusion --- p.35 / Chapter 6.2 --- Further Research Topic --- p.38 / Appendix A --- p.39 / Appendix B --- p.46 / Bibliography --- p.55
4

Empirical likelihood method for segmented linear regression

Unknown Date (has links)
For a segmented regression system with an unknown change-point over two domains of a predictor, a new empirical likelihood ratio test statistic is proposed to test the null hypothesis of no change. The proposed method is a non-parametric method which releases the assumption of the error distribution. Under the null hypothesis of no change, the proposed test statistic is shown empirically Gumbel distributed with robust location and scale parameters under various parameter settings and error distributions. Under the alternative hypothesis with a change-point, the comparisons with two other methods (Chen's SIC method and Muggeo's SEG method) show that the proposed method performs better when the slope change is small. A power analysis is conducted to illustrate the performance of the test. The proposed method is also applied to analyze two real datasets: the plasma osmolality dataset and the gasoline price dataset. / by Zhihua Liu. / Thesis (Ph.D.)--Florida Atlantic University, 2011. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 200?. Mode of access: World Wide Web.
5

A new sequential test for change point detection in time series. / CUHK electronic theses & dissertations collection

January 2012 (has links)
本文論述了一種全新的快速探測時間序列中結構性突變點的過程。我們應用了一個新的統計量,平均時間常方差,作為樣本協方差結構改變的代理變量。平均時間常方差也可以表現為所有協方差函數的和。吳(2009)提出了一種能夠遞歸計算平均時間常方差估計值的算法並被我們應用在這篇文,其有效更新計算及記憶複雜度均為O(1) 。在這篇文章中,我們研究了平均時間常方差估計值的漸進分佈並設立了一組置信帶(confidence bands) 來監視時間序列是否有突變發生。根據蒙特卡洛模擬,我們發現這種測試方法有很好的統計特性規模(size) 和檢驗力(power)。微陣列數據(Microarray data) 的實例在我們的文章中也進行了展示。我們的算法只在1. 86GHz的處理器中,需要約2秒就能夠檢測長度為10000 的序列。 / This paper proposes a new and fast change point detection procedure for time series. We develop a new proxy for the change in the (sample) covariance structure, the Time Average Variance Constant (TAVC), which could be expressed as the summation of all the auto-covariance functions. Wu (2009)'s algorithm is implemented to compute the estimate of TAVC recursively with an efficient updating computational and memory complexity of O(1). In this article, we study an asymptotic distribution of TAVC estimator and construct condence bands to monitor whether a change happens in a time series. We show the good size and power properties of the procedure based on Monte Carlo Simulation. Illustrations using microarray data are presented. Our algorithm only takes~2s on a single 1.86GHz processor with a sequence of length 10,000. / Detailed summary in vernacular field only. / Jin, Yong. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 38-45). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts also in Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 2 --- Time Average Variance Constant --- p.6 / Chapter 2.1 --- What is Time Average Variance Constant? --- p.6 / Chapter 2.2 --- Another Look at TAVC --- p.7 / Chapter 2.3 --- Estimation of Time Average Variance Constant --- p.7 / Chapter 2.3.1 --- Algorithm 1: Wu(2009) --- p.8 / Chapter 2.3.2 --- Algorithm 2: Wu(2009) --- p.8 / Chapter 3 --- Behavior of the Sample Auto-Covariance Structure for a Change in Mean --- p.11 / Chapter 3.1 --- Problem Formulation --- p.11 / Chapter 3.2 --- CUSUM Test --- p.12 / Chapter 3.3 --- Behavior of the Sample Auto-Covariance Structure --- p.14 / Chapter 4 --- Change-Point Tests and Algorithms --- p.17 / Chapter 4.1 --- Asymptotic Normality --- p.17 / Chapter 4.2 --- A Change Point Detection Procedure based on TAVC --- p.22 / Chapter 4.2.1 --- Algorithm 3 --- p.23 / Chapter 4.2.2 --- An example: AR(1) Model with p = 0.4 --- p.24 / Chapter 4.2.3 --- Size And Power --- p.26 / Chapter 4.3 --- Array CGH data Example --- p.28 / Chapter 5 --- Conclusion --- p.31 / Chapter 6 --- Appendix --- p.32 / Chapter 6.1 --- Proof of Theorem 3.1 --- p.32 / Bibliography --- p.38
6

Change point estimation for threshold autoregressive (TAR) model.

January 2012 (has links)
時間序列之變點鬥檻模型是一種非線性的模型。此論文探討有關該模型之參數估計,同時對其參數估計作出統計分析。我們運用了遺傳式計算機運算來估計這些參數及對其作出研究。我們利用了MDL來對比不同的變點門檻模型,同時我們也利用了MDL來選取對應的變點門檻模型。 / This article considers the problem of modeling non-linear time series by using piece-wise TAR model. The numbers of change points, the numbers of thresholds and the corresponding order of AR in each piecewise TAR segments are assumed unknown. The goal is to nd out the “best“ combination of the number of change points, the value of threshold in each time segment, and the underlying AR order for each threshold regime. A genetic algorithm is implemented to solve this optimization problem and the minimum description length principle is applied to compare various segmented TAR. We also show the consistency of the minimal MDL model selection procedure under general regularity conditions on the likelihood function. / Detailed summary in vernacular field only. / Tang, Chong Man. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 45-47). / Abstracts also in Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Introduction --- p.1 / Chapter 2 --- Minimum Description Length for Pure TAR --- p.4 / Chapter 2.1 --- Model selection using Minimum Description Length for Pure TAR --- p.4 / Chapter 2.1.1 --- Derivation of Minimum Description Length for Pure TAR --- p.5 / Chapter 2.2 --- Optimization Using Genetic Algorithms (GA) --- p.7 / Chapter 2.2.1 --- General Description --- p.7 / Chapter 2.2.2 --- Implementation Details --- p.9 / Chapter 3 --- Minimum Description Length for TAR models with structural change --- p.13 / Chapter 3.1 --- Model selection using Minimum Description Length for TAR models with structural change --- p.13 / Chapter 3.1.1 --- Derivation of Minimum Description Length for TAR models with structural change --- p.14 / Chapter 3.2 --- Optimization Using Genetic Algorithms --- p.17 / Chapter 4 --- Main Result --- p.20 / Chapter 4.1 --- Main results --- p.20 / Chapter 4.1.1 --- Model Selection using minimum description length --- p.21 / Chapter 5 --- Simulation Result --- p.24 / Chapter 5.1 --- Simulation results --- p.24 / Chapter 5.1.1 --- Example of TAR Model Without Structural Break --- p.24 / Chapter 5.1.2 --- Example of TAR Model With Structural Break I --- p.26 / Chapter 5.1.3 --- Example of TAR Model With Structural Break II --- p.29 / Chapter 6 --- An empirical example --- p.33 / Chapter 6.1 --- An empirical example --- p.33 / Chapter 7 --- Consistency of the CLSE --- p.36 / Chapter 7.1 --- Consistency of the TAR parameters --- p.36 / Chapter 7.1.1 --- Consistency of the estimation of number of threshold --- p.36 / Chapter 7.1.2 --- Consistency of the change point parameters --- p.43 / Bibliography --- p.45
7

Non-parametric, non-sequential change-point analysis /

Pouliot, William J., January 1900 (has links)
Thesis (Ph. D.)--Carleton University, 2002. / Includes bibliographical references (p. 192-195). Also available in electronic format on the Internet.
8

Robust change detection and change point estimation for poisson count processes

Perry, Marcus B. Pignatiello, Joseph J., January 2004 (has links)
Thesis (Ph. D.)--Florida State University, 2004. / Advisor: Dr. Joseph Pignatiello, Jr., Florida State University, College of Engineering, Dept. of Industrial Engineering. Title and description from dissertation home page (viewed Sept. 23, 2004). Includes bibliographical references.
9

Detecting change points in time series using the Bayesian approach with perfect simulation : a thesis presented for the degree of Master of Science in Statistics at the University of Canterbury, Christchurch, New Zealand /

Richens, Andrew Stephen. January 1900 (has links)
Thesis (M. Sc.)--University of Canterbury, 2008. / Typescript (photocopy). "8 February 2008." Includes bibliographical references (p. 112-114). Also available via the World Wide Web.
10

Segmented regression : a robust approach /

Healey, Brian, January 2004 (has links)
Thesis (M.A.S.)--Memorial University of Newfoundland, 2004. / Restricted until October 2005. Bibliography: leaves 92-100.

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