Asymptotics for sliced average variance estimation

In this paper, we systematically study the consistency of sliced average variance estimation (SAVE). The findings reveal that when the response is continuous, the asymptotic behavior of SAVE is rather different from that of sliced inverse regression (SIR). SIR can achieve $\sqrt{n}$ consistency even when each slice contains only two data points. However, SAVE cannot be $\sqrt{n}$ consistent and it even turns out to be not consistent when each slice contains a fixed number of data points that do not depend on n, where n is the sample size. These results theoretically confirm the notion that SAVE is more sensitive to the number of slices than SIR. Taking this into account, a bias correction is recommended in order to allow SAVE to be $\sqrt{n}$ consistent. In contrast, when the response is discrete and takes finite values, $\sqrt{n}$ consistency can be achieved. Therefore, an approximation through discretization, which is commonly used in practice, is studied. A simulation study is carried out for the purposes of illustration.Comment: Published at http://dx.doi.org/10.1214/009053606000001091 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Genotoxicity Disrupts Intestinal Proliferating Cells

Many bacterial infections have been shown to cause DNA damage in host cells, and a number of pathogens can directly damage host DNA by producing genotoxins. Due to the importance of maintaining genomic integrity for cellular function, cells possess a coordinated DNA damage response (DDR) mechanism to sense damage in DNA and generate a signal amplification cascade to activate DNA repair mediators. Our study has shown that cytolethal distending toxins (CDTs), a genotoxin secreted by mucosal pathogenic bacteria, is responsible for DNA damage and thus prolonged cell cycle arrest in intoxicated intestinal proliferating crypt cells. Our data support that CDT intoxication results in a large increase in activated H2AX level, an early DNA damage signal, and in cellular p53 levels, a major cellular protein responsible for cell cycle arrest in response to DNA damage. Also, we found that CDT-mediated DNA damage results in reduction of a transcription factor involved in the differentiation potential of intestinal proliferating cells, Snai1, which is responsible for lineage allocation in differentiating cells. In order to evaluate whether pathogen-independent DNA damaging agents can lead to reduction in cellular levels of Snai1 in normal human intestinal proliferating cells, used three DNA damage agents, including 5-fluorouracil and etoposide, each of which causes DNA damage in different ways. Our data support that CDT-independent DNA damage lead to dose-dependent reduction in Snai1 level. These experiments enhance our understanding of potential side effects of widely used chemotherapeutics on epithelial barrier homeostasis and overall innate immunity.Ope

Inequality and Poverty in China during Reform

This paper provides an overview of the evolution of income inequality and poverty in China from 1987 to 2002, documenting significant increases of inequality within China's urban and rural populations. In rural areas, increased inequality is primarily related to the disequalizing role of non-agricultural self-employment income and the slow growth in agricultural income from the mid-1990s onward. Poverty persists, and tied in part to slow growth in agricultural commodity prices. In urban areas, the declining role of subsidies and entitlements, the increase in wage inequality, and the layoffs during restructuring have fueled the growth in inequality within urban areas. Poverty levels, however, are very low. China should give more emphasis on education, training, and other human development efforts in its poverty reduction strategy since return to education increased rapidly and became a major source of inequality. A nationwide "social safety net" and an effective redistributive taxation system should be adopted and implemented to ensure that the poor can benefit from the fruits of rapid economic growth.Income inequality, poverty, welfare, growth, reform, transition, policy, China

Smooth principal component analysis for high dimensional data

This paper considers smooth principle component analysis for high dimensional data with very large dimensional observations p and moderate number of individuals N. Our setting is similar to traditional PCA, but we assume the factors are smooth and design a new approach to estimate them. By connecting with Singular Value Decomposition subjected to penalized smoothing, our algorithm is linear in the dimensionality of the data, and it also favors block calculations and sequential access to memory. Different from most existing methods, we avoid extracting eignefunctions via smoothing a huge dimensional covariance operator. Under regularity assumptions, the results indicate that we may enjoy faster convergence rate by employing smoothness assumption. We also extend our methods when each subject is given multiple tasks by adopting the two way ANOVA approach to further demonstrate the advantages of our approach

LIKELIHOOD RATIO TESTS FOR THE MEAN STRUCTURE OF CORRELATED FUNCTIONAL PROCESSES

The paper introduces a general framework for testing hypotheses about the structure of the mean function of complex functional processes. Important particular cases of the proposed framework are: 1) testing the null hypotheses that the mean of a functional process is parametric against a nonparametric alternative; and 2) testing the null hypothesis that the means of two possibly correlated functional processes are equal or differ by only a simple parametric function. A global pseudo likelihood ratio test is proposed and its asymptotic distribution is derived. The size and power properties of the test are confirmed in realistic simulation scenarios. Finite sample power results indicate that the proposed test is much more powerful than competing alternatives. Methods are applied to testing the equality between the means of normalized δ-power of sleep electroencephalograms of subjects with sleep-disordered breathing and matched controls

Fast Bivariate P-splines: the Sandwich Smoother

We propose a fast penalized spline method for bivariate smoothing. Univariate Pspline smoothers Eilers and Marx (1996) are applied simultaneously along both coordinates. The new smoother has a sandwich form which suggested the name “sandwich smoother” to a referee. The sandwich smoother has a tensor product structure that simplifies an asymptotic analysis and it can be fast computed. We derive a local central limit theorem for the sandwich smoother, with simple expressions for the asymptotic bias and variance, by showing that the sandwich smoother is asymptotically equivalent to a bivariate kernel regression estimator with a product kernel. As far as we are aware, this is the first central limit theorem for a bivariate spline estimator of any type. Our simulation study shows that the sandwich smoother is orders of magnitude faster to compute than other bivariate spline smoothers, even when the latter are computed using a fast GLAM (Generalized Linear Array Model) algorithm, and comparable to them in terms of mean squared integrated errors. We extend the sandwich smoother to array data of higher dimensions, where a GLAM algorithm improves the computational speed of the sandwich smoother. One important application of the sandwich smoother is to estimate covariance functions in functional data analysis. In this application, our numerical results show that the sandwich smoother is orders of magnitude faster than local linear regression. The speed of the sandwich formula is important because functional data sets are becoming quite large

Does Index Futures Trading Reduce Volatility in the Chinese Stock Market? A Panel Data Evaluation Approach

This paper investigates the effect of introducing index futures trading on the spot price volatility in the Chinese stock market. We employ a recently developed panel data policy evaluation approach (Hsiao et al. 2011) to construct counterfactuals of the spot market volatility, based mainly on cross-sectional correlations between the Chinese and international stock markets. This new method does not need to specify a particular regression or a time series model for the volatility process around the introduction date of index futures trading, and thus avoids the potential omitted variable bias caused by uncontrolled market factors in the existing literature. Our results provide empirical evidence that the introduction of index futures trading significantly reduces the volatility of the Chinese stock market, which is robust to different model selection criteria and various prediction approaches.