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Functional central limit theorems for supercritical superprocesses
Functional central limit theorem supercritical superprocess excursion measures of superprocesses
2016/1/20
In this paper, we establish some functional central limit theorems for a large class of general supercritical superprocesses with spatially dependent branching mechanisms satisfying a second moment co...
Feature Screening for Ultrahigh Dimensional Categorical Data with Applications
Feature Screening Pearson’s Chi-Square Test Screening Consisten- cy Search Engine Marketing Text Classification Ultrahigh Dimensional Data
2016/1/20
Ultrahigh dimensional data with both categorical responses and categorical covari-ates are frequently encountered in the analysis of big data, for which feature screening has become an indispensable s...
Optimal Designs for the Proportional Interference Model
Approximate design theory equivalence theorem interference model optimal design proportional model
2016/1/20
The interference model has been widely used and studied in block experiments where the treatment for a particular plot has effects on its neighbor plots. In this paper, we study optimal circular desig...
Estimating Mixture of Gaussian Processes by Kernel Smoothing
Identifiability EM algorithm Kernel regression Gaussian process Functional principal component analysis
2016/1/20
When the functional data are not homogeneous, e.g., there exist multiple classes of func-tional curves in the dataset, traditional estimation methods may fail. In this paper, we propose a new estimati...
Optimality of Pairwise Blocked Definitive Screening Designs
Blocking Definitive screening design Optimality Generalized minimum aberration Fold-over
2016/1/20
Definitive screening designs are a new class of three-level designs which are shown superior to the classical central composite designs in response surface methodology. They can be constructed by inse...
CreditRisk Model with Dependent Risk Factors
CreditRisk + model conditional independence dependent risk factors
2016/1/20
The CreditRisk + model is widely used in industry for computing the loss of a credit port-folio. The standard CreditRisk + model assumes independence among a set of common risk factors, a simplified a...
Testing the Diagonality of a Large Covariance Matrix in a Regression Setting
Bias-Corrected Test Covariance Diagonality Test High Di- mensional Data Multivariate Analysis
2016/1/20
In multivariate analysis, the covariance matrix associated with a set of vari-ables of interest (namely response variables) commonly contains valuable infor-mation about the dataset. When the dimensio...
Shuffle of min’s random variable approximations of bivariate copulas’realization
random variable approximations bivariate copulas realization
2016/1/20
The comonotonicity and countermonotonicity provide intuitive upper and lower depen-dence relationship between random variables. This paper constructs the shuffle of min’s ran-domvariableapproximations...
这是一个最好的时代。移动互联网技术为从业者提供了有关人们言行举止、社交关系和地里位置等各种丰富详细的数据，价值巨大。这也是一个最坏的时代。面对海量数据，绝大多数从业者却无法从中发掘出有用的信息，难以实现从数据到价值的转换。这不是一两个人面对的困境，而是绝大多数人遭遇的瓶颈，因此，我们需要检讨：这是怎么回事，问题出在哪个环节？
Spatial Panel Data Models. Oxford Handbook of Panel Data
Spatial Panel Data Models Oxford Handbook Panel Data
2016/1/20
The consideration of interactions among regions or agents has become increasingly important in various fields of economics. In public economics, a state government’s cigarettes tax rate will be influe...
Efficient GMM Estimation of Spatial Dynamic Panel Data Models
Spatial autoregression Dynamic panels Fixed effects
2016/1/20
In this paper we derive the asymptotic properties of GMM estimators for the spatial dynamic panel data model with fixed effects when n is large, and T can be large, but small relative to n. The GMM es...
Estimation of Spatial Panel Data Models with Time Varying Spatial Weights Matrices
Spatial autoregression Panel data Time varying spatial weights matrices Fixed e¤ects Maximum likelihood Impact analysis
2016/1/20
This paper investigates the quasi-maximum likelihood (QML) estimation of spatial panel data models where spatial weights matrices can be time varying. We show that QML estimate is consistent and asymp...
Identification of spatial panel Durbin models
Spatial autoregression Durbin regressors Spatial VAR Dynamic panel Fixed e¤ects Random e¤ects
2016/1/20
Identi…cation of a spatial Durbin model is a concern in the spatial econometrics literature. The concern is similar to the identi…cation of the endogenous e¤ect, the contextual e¤ect and correlation e...
An allosteric model of the inositol trisphosphate receptor with nonequilibrium binding
inositol trisphosphatereceptor adaptation overshoot nonequilibrium Monod- Wyman-Changeux model
2016/1/20
Theinositoltrisphosphatereceptor(IPR) is acrucialionchannelthat regulatestheCa 2+ influx from the endoplasmic reticulum (ER) to the cytoplasm. A thorough study of the IPR channel contributes to a bett...