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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...
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...
Efficient GMM Estimation of Spatial Dynamic Panel Data Models
Spatial autoregression Dynamic panels Fixed effects Generalized method of moment
2016/1/26
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
2016/1/26
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...
Estimation in semiparametric models with missing data
Copulas imputation kernel smoothing missing at random nuisance function partially linear model
2016/1/25
We propose a novel varying coefficient model, called princi-pal varying coefficient model (PVCM), by characterizing the varying coeffi-cients through linear combinations of a few principal functions. ...
Evaluation of somatic copy number estimation tools for whole-exome sequencing data
CNV prediction Somatic alterations The Cancer Genome Atlas CNV algorithms
2016/1/20
Evaluation of somatic copy number estimation tools for whole-exome sequencing data.
Bias Correction for Fixed Effects Spatial Panel Data Models
Bootstrap Spatial Panel Individual Fixed Effects Time Fixed Effects
2016/1/20
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...
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 for spatial dynamic panel data with fixed effects: the case of spatial cointegration
Dynamic panels Fixed e¤ects Quasi-maximum likelihood estima- tion Bias correction Generalized method of moments Spatial cointegration
2016/1/19
Yu, de Jong and Lee (2008) establish asymptotic properties of quasi-maximum likelihood estimators for a stable spatial dynamic panel model with …xed e¤ects when both the number of individuals n and th...
Effcient GMM estimation of spatial dynamic panel data models with fixed effects
Spatial autoregression Dynamic panels Fixed e¤ects Generalized method of moment Many moments
2016/1/19
In this paper we derive the asymptotic properties of GMM estimators for the spatial dynamic panel data model with …xed e¤ects when n is large, and T can be large, but small relative to n. The GMM esti...
A Hierarchical Bayesian Approach for Aerosol Retrieval Using MISR Data
Bayesian Approach MISR Data Retrieval
2011/7/19
Atmospheric aerosols can cause serious damage to human health and life expectancy. Using the radiances observed by NASA's Multi-angle Imaging SpectroRadiometer (MISR), the current MISR operational alg...
Efficient Gaussian Process Regression for Large Data Sets
Bayesian Compressive Sensing Dimension Reduction
2011/7/6
Gaussian processes (GPs) are widely used in nonparametric regression, classification and spatio-temporal modeling, motivated in part by a rich literature on theoretical properties.
Causality as a unifying approach between activation and connectivity analysis of fMRI data
Causality activations functional connectivity fMRI
2011/3/24
This paper indicates causality as the tool that unifies the analysis of both activations and connectivity of brain areas, obtained with fMRI data. Causality analysis is commonly applied to study conne...
Semi-supervised logistic discrimination for functional data
EM algorithm Functional data analysis Model selec-tion Regularization Semi-supervised learning
2011/3/24
Multi-class classification methods based on both labeled and unlabeled functional data sets are discussed. We present semi-supervised logistic models for classification in the context of functional da...
A Hierarchical Model for Aggregated Functional Data
Bayes'theorem B-splines Covariance function Gaussian process
2011/3/21
In many areas of science one aims to estimate latent sub-population mean curves based only on observations of aggregated population curves. By aggregated curves we mean linear combination of functiona...