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CENTRAL LIMIT THEOREMS FOR FOUR NEW TYPES OF U-DESIGNS
Central limit theorem correlation controlled U-design nested U-design sliced U-design strong orthogonal array based U-design
2016/1/26
Orthogonal array based Latin hypercube designs, also called U-designs, have been popularly adopted in designing a computer exper-iment. Nested U-designs, sliced U-designs, strong orthogonal array base...
Identification of universally optimal circular designs for the interference model
Approximate design theory circular design interference model linear equations system universal optimality
2016/1/26
Many applications of block designs exhibit neighbor and edge ef-fects. A popular remedy is to use the circular design coupled with the interference model. The search for optimal or efficient designs h...
Direct Regression Modelling of High-order Moments in Big Data
Big data Higher-order moment U-statistics Estimating equation Divide-and-conquer
2016/1/26
Big data problems present great challenges to statisti-cal analyses, especially from the computational side. In this paper, we consider regression estimation of high-order mo-ments in big data problem...
Evaluation of somatic copy number estimation tools for whole-exome sequencing data
CNV prediction Somatic alterations The Cancer Genome Atlas CNV algorithms
2016/1/26
Evaluation of somatic copy number estimation tools for whole-exome sequencing data.
Estimating Spatial Autocorrelation with Sampled Network Data
NetworkDataAnalysis Paired Maximum Likelihood Estimator
2016/1/26
Spatial autocorrelation is a parameter of importance for network data analysis. To estimate spatial autocorrelation, maximum likelihood has been popularly used. However, its rigorous implementation re...
Efficient Estimation of Nonparametric Simultaneous Equations Models
Local Polynomial Regression Nonparametric Additive Models Structural Models Instrumental Variables
2016/1/26
This paper defines a new procedure to efficiently estimate nonparametric simultaneous e-quations models that have been explored by Newey et al (1999) and Su and Ullah (2008).The proposed estimation pr...
Enhancing Estimation for Interest Rate Diffusion Models with Bond Prices
Interest Rate Models Affine Term Structure Bond Prices Market Price of Risk Combined Estimation Parameter Estimation
2016/1/26
We consider improving estimating parameters of diffusion processes for interest rates by incorporating information in bond prices. This is designed to improve the estimation of the drift parameters, w...
Law of large numbers for branching symmetric Hunt processes with measure-valued branching rates
Law of large numbers branching Hunt processes spine approach h-transform spectral gap
2016/1/26
We establish weak and strong law of large numbers for a class of branching symmetric Hunt processes with the branching rate being a smooth measure with respect to the underlying Hunt process, and the ...
Strong law of large numbers for supercritical superprocesses under second moment condition
superprocess scaling limit theorem Hunt process spec- tral gap h-transform martingale measure
2016/1/26
Strong law of large numbers for supercritical superprocesses under second moment condition.
Boundary Harnack principle and gradient estimates for fractional Laplacian perturbed by non-local operators
Harmonic function boundary Harnack principle gradient estimate non-local operator Green function Poisson kernel
2016/1/26
Boundary Harnack principle and gradient estimates for fractional Laplacian perturbed by non-local operators.
Bias Correction for Fixed Effects Spatial Panel Data Models
Bootstrap Spatial Panel Individual Fixed Effects Time Fixed Effects
2016/1/26
This paper examines the finite sample properties of the quasi maximum likelihood (QML) esti-mators of the fixed effects spatial panel data (FE-SPD) models of Lee and Yu (2010). Following the general b...
Spatial Weights Matrix Selection and Model Averaging for Spatial Autoregressive Models
Model Selection Model Averaging Spatial Econometrics Spatial Autoregressive
2016/1/26
Spatial econometrics relies on spatial weights matrix to specify the cross sectional depen-dence, which might not be unique. This paper proposes a model selection procedure to choose an optimal weight...
Counting and Exploring Sizes of Markov Equivalence Classes of Directed Acyclic Graphs
Directed acyclic graphs Markov equivalence class Size distribution Causal- ity
2016/1/26
When learning a directed acyclic graph (DAG) model via observational data, one gener-ally cannot identify the underlying DAG, but can potentially obtain a Markov equivalence class. The size (the numbe...
High Dimensional Generalized Empirical Likelihood for Moment Restrictions with Dependent Data
Generalized empirical likelihood High dimensionality Penalized likelihood Variable selec- tion
2016/1/26
This paper considers the maximum generalized empirical likelihood (GEL) estimation and inference on parameters identified by high dimensional moment restrictions with weakly dependent data when the di...
FUNCTIONAL COEFFICIENT MOVING AVERAGE MODEL WITH APPLICATIONS TO FORECASTING CHINESE CPI
Moving Average model functional coefficient model fore- casting Consumer Price Index
2016/1/26
This article establishes the functional coefficient moving average mod-el (FMA), which allows the coefficient of the classical moving average model to adapt with a covariate. The functional coefficien...