Multiple Change-point Detection: a Selective Overview

Very long and noisy sequence data arise from biological sciences to social science including high throughput data in genomics and stock prices in econometrics. Often such data are collected in order to identify and understand shifts in trend, e.g., from a bull market to a bear market in finance or from a normal number of chromosome copies to an excessive number of chromosome copies in genetics. Thus, identifying multiple change points in a long, possibly very long, sequence is an important problem. In this article, we review both classical and new multiple change-point detection strategies. Considering the long history and the extensive literature on the change-point detection, we provide an in-depth discussion on a normal mean change-point model from aspects of regression analysis, hypothesis testing, consistency and inference. In particular, we present a strategy to gather and aggregate local information for change-point detection that has become the cornerstone of several emerging methods because of its attractiveness in both computational and theoretical properties.Comment: 26 pages, 2 figure

Nonparametric estimation of genewise variance for microarray data

Estimation of genewise variance arises from two important applications in microarray data analysis: selecting significantly differentially expressed genes and validation tests for normalization of microarray data. We approach the problem by introducing a two-way nonparametric model, which is an extension of the famous Neyman--Scott model and is applicable beyond microarray data. The problem itself poses interesting challenges because the number of nuisance parameters is proportional to the sample size and it is not obvious how the variance function can be estimated when measurements are correlated. In such a high-dimensional nonparametric problem, we proposed two novel nonparametric estimators for genewise variance function and semiparametric estimators for measurement correlation, via solving a system of nonlinear equations. Their asymptotic normality is established. The finite sample property is demonstrated by simulation studies. The estimators also improve the power of the tests for detecting statistically differentially expressed genes. The methodology is illustrated by the data from microarray quality control (MAQC) project.Comment: Published in at http://dx.doi.org/10.1214/10-AOS802 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Study on cyclic loading and unloading characteristics of remolded saturated soft soil

This paper described a continuous load one-dimensional K0 consolidation apparatus developed and improved, conducted an axial cyclic loading and unloading test of saturated soft clay. It can be known from the experimental comparison that during the unloading period, a stress strain curve of saturated soft clay is made hyperbolic. During the reloading period, when the loading quantity is less than the unloading quantity, the curve is hyperbolic, and when the loading quantity is greater than unloading quantity the curve is a straight line which keeps hardening. The plastic deformation and elastic deformation of test samples produced in the test have linear relation with the unloading level. On the basis of the original constitutive relation, axial circulation loading and unloading constitutive equation have been established using the loading axial stresses, initial tangent modulus, maximum unloading axial strain and its initial secant modulus as parameters. The reliability of equations was verified as well. The analysis of various plastic hysteresis reveals that as the unloading stress level increases, the hysteresis increases too and conforms to the quadratic curve relationship. This provides a certain engineering practice value for the strength and deformation characteristics of soft soil under cyclic loading

Dynamics of Terrestrial Ecosystems, Water, and Climate in The United States

Water, climate, and vegetation all play major roles in keeping ecosystems alive. By looking at satellite gathered data through NCL, (a unix based coding language) patterns, trends, and change over time, or a lack thereof, were observed. A warming trend in the United States was noticed. The Leaf Area Index suffered an important drop in the American South, Eastern Texas, and the Bay Area, California. Precipitation, overall, stayed about the same, seeing drops in some areas, like the American South West, or increases,in the American Midwest as well as the North East. Oddly, Texas and the American South had significant rainfall over time. Also, there was an increase in vegetation in Arizona, Nevada, and Eastern California,despite the drop in precipitation in these areas

Association of α-Adducin and G-Protein β3 Genetic Polymorphisms with Hypertension: A Meta-Analysis of Chinese Populations

BACKGROUND: Mounting evidence has suggested that α-adducin and G-protein β3 (GNB3) genes are logical candidates for salt-sensitive hypertension. Some, but not all, studies have reported that α-adducin G460T and GNB3 C825T polymorphisms may influence the risk of the disease. To comprehensively address this issue, we performed a meta-analysis to evaluate the influence of these two polymorphisms on hypertension and potential biases in Chinese. METHODS: Data were analyzed using Stata (v11.0) and random-effects model was applied irrespective of between-studies heterogeneity, which was evaluated via subgroup and meta-regression analyses. Study quality was assessed in duplicate. Publication bias was weighed using Egger's test and funnel plot. RESULTS: 36 study populations totaling 9042 hypertensive patients and 8399 controls were finally identified. Overall, in allelic/genotypic/dominant/recessive models, no significant association was identified for both G460T and C825T polymorphisms (P>0.05) and there was possible heterogeneity (I(2)>25%). Subgroup analyses by study design indicated that the magnitude of association in population-based studies was marginally significantly strengthened for α-adducin G460T allelic model (OR = 1.12; 95% CI: 1:00-1.25; P = 0.043). Moreover, subgroup analyses by geographic distribution indicated comparison of 825T with 825C yielded a marginally significant increased risk in southern Chinese only (OR = 1.48; 95% CI: 1.01-2.16; P = 0.045). Further meta-regression analyses showed that geographic regions were a significant source of between-study heterogeneity for both polymorphisms. There was a possibility of publication bias for G460T, but not for C825T. CONCLUSIONS: Our overall results suggest null association of α-adducin G460T and GNB3 C825T polymorphisms with hypertension in Chinese but indicate local marginal significance of C825T, as a putative salt-sensitive switch, in southern Chinese