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"James, Nicholas A."
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Nonparametric Approach for Multiple Change Point Analysis of Multivariate Data
Change point analysis has applications in a wide variety of fields. The general problem concerns the inference of a change in distribution for a set of time-ordered observations. Sequential detection is an online version in which new data are continually arriving and are analyzed adaptively. We are concerned with the related, but distinct, offline version, in which retrospective analysis of an entire sequence is performed. For a set of multivariate observations of arbitrary dimension, we consider nonparametric estimation of both the number of change points and the positions at which they occur. We do not make any assumptions regarding the nature of the change in distribution or any distribution assumptions beyond the existence of the αth absolute moment, for some α ∈ (0, 2). Estimation is based on hierarchical clustering and we propose both divisive and agglomerative algorithms. The divisive method is shown to provide consistent estimates of both the number and the location of change points under standard regularity assumptions. We compare the proposed approach with competing methods in a simulation study. Methods from cluster analysis are applied to assess performance and to allow simple comparisons of location estimates, even when the estimated number differs. We conclude with applications in genetics, finance, and spatio-temporal analysis. Supplementary materials for this article are available online.
Journal Article
تعليم الأطفال ذوي الحاجات الخاصة
يعد كتاب تعليم الأطفال ذوي الحاجات الخاصة للمؤلف صموئيل كيرك وزملائه من المراجع القيمة حيث يشتمل على آخر التطورات والمستجدات في مجال تخصص التربية الخاصة. ويمكن للقارئ إن يلاحظ بأن الكتاب تطرق لمجالات وفئات التربية الخاصة من خلال مناح ونماذج عدة أهمها : نموذج معالجة المعلومات، وآخر الأبحاث والدراسات العصبية والجينية، أهمية التدخل المبكر ومرحلة الطفولة المبكرة، بالإضافة إلى موضوع الدمج الشامل وأهمية توظيف منحى الاستجابة للتدخل، ويمكن للقارئ وعبر الدخول إلى الموقع الالكتروني للكتاب إن يتفحص آخر المستجدات المتعلقة بالأساليب التربوية والتكنولوجيا المساندة.
BOOK
Offering a Celebrity Experimental Treatment
To the Editor:
On November 29, 1992, Dennis Byrd, a football player with the New York Jets, suffered a serious spinal cord injury when he collided with a teammate during a game. According to reports by the news media, Byrd was treated at Lenox Hill Hospital in New York with an experimental drug
1
,
2
. These reports dismay researchers such as myself, who are conducting randomized, controlled trials of treatments for such injuries. The drug, GM-1 ganglioside, is an experimental therapy for spinal injury
3
. It has shown sufficient promise in a pilot study to warrant investigation in an ongoing . . .
Journal Article
The shape of the river : long-term consequences of considering race in college and university admissions
First published in 1998, William Bowen and Derek Bok's The Shape of the River became an immediate landmark in the debate over affirmative action in America. It grounded a contentious subject in concrete data at a time when arguments surrounding it were characterized more by emotion than evidence--and it made a forceful case that race-conscious admissions were successfully helping to promote equal opportunity. Today, the issue of affirmative action remains unsettled. Much has changed, but The Shape of the River continues to present the most compelling data available about the effects of affirmative action. Now with a new foreword by Nicholas Lemann and an afterword by Derek Bok, The Shape of the River is an essential text for anyone seeking to understand race-conscious admissions in higher education.
Book
Change Points via Probabilistically Pruned Objectives
The concept of homogeneity plays a critical role in statistics, both in its applications as well as its theory. Change point analysis is a statistical tool that aims to attain homogeneity within time series data. This is accomplished through partitioning the time series into a number of contiguous homogeneous segments. The applications of such techniques range from identifying chromosome alterations to solar flare detection. In this manuscript we present a general purpose search algorithm called cp3o that can be used to identify change points in multivariate time series. This new search procedure can be applied with a large class of goodness of fit measures. Additionally, a reduction in the computational time needed to identify change points is accomplish by means of probabilistic pruning. With mild assumptions about the goodness of fit measure this new search algorithm is shown to generate consistent estimates for both the number of change points and their locations, even when the number of change points increases with the time series length. A change point algorithm that incorporates the cp3o search algorithm and E-Statistics, e-cp3o, is also presented. The only distributional assumption that the e-cp3o procedure makes is that the absolute \\(\\alpha\\)th moment exists, for some \\(\\alpha\\in(0,2)\\). Due to this mild restriction, the e-cp3o procedure can be applied to a majority of change point problems. Furthermore, even with such a mild restriction, the e-cp3o procedure has the ability to detect any type of distributional change within a time series. Simulation studies are used to compare the e-cp3o procedure to other parametric and nonparametric change point procedures, we highlight applications of e-cp3o to climate and financial datasets.
Paper
Statistical Measures of Dependence for Financial Data
This chapter provides the statistical measures of dependence for financial data. The analysis of financial and econometric data is typified by non-Gaussian multivariate observations that exhibit complex dependencies: heavy-tailed and skewed marginal distributions are commonly encountered; serial dependence, such as autocorrelation and conditional heteroscedasticity. When data are assumed to be jointly Gaussian, all dependence is linear, and therefore only pairwise among the variables. In this setting, Pearson's product-moment correlation coefficient uniquely characterizes the sign and strength of any such dependence. The chapter shows that copulas can be used to model the dependence between random variables. It turns our attention to the dependence structure itself, and when appropriate makes connections to copulas. The chapter describes different types of dependence, and then provides theoretical background.
Book Chapter
ecp: An R Package for Nonparametric Multiple Change Point Analysis of Multivariate Data
There are many different ways in which change point analysis can be performed, from purely parametric methods to those that are distribution free. The ecp package is designed to perform multiple change point analysis while making as few assumptions as possible. While many other change point methods are applicable only for univariate data, this R package is suitable for both univariate and multivariate observations. Estimation can be based upon either a hierarchical divisive or agglomerative algorithm. Divisive estimation sequentially identifies change points via a bisection algorithm. The agglomerative algorithm estimates change point locations by determining an optimal segmentation. Both approaches are able to detect any type of distributional change within the data. This provides an advantage over many existing change point algorithms which are only able to detect changes within the marginal distributions.
Paper