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Tests for High Dimensional Generalized Linear Models
Generalized Linear Model Gene-Sets High Dimensional Covariate Nuisance Parameter U-statistics
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2016/1/26
We consider testing regression coefficients in high dimensional generalized linear mod-els. By modifying a test statistic proposed by Goeman et al. (2011) for large but fixed dimensional settings, we ...
The Influence from the Past: Organizational Imprinting and Firms’ Compliance with Social Insurance Policies in China
Social insurance provision for workers Organizational imprinting Institutional logics
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2016/1/26
Using a nationwide survey of randomly selec-ted manufacturing firms in representative Chinese cities,we examine how firms’ compliance with social insurance policies is shaped by their historical impri...
Backgroud: Epistatic Miniarray Profiles (EMAP) enables the research of genetic interaction as an importan-t method to construct large-scale genetic interaction network. However, high proportion of mis...
High dimensional stochastic regression with latent factors, endogeneity and nonlinearity
α-mixing dimension reduction instrument variables nonstationarity time series
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2016/1/25
We consider a multivariate time series model which represents a high dimensional vector process as a sum of three terms: a linear regression of some observed regressors,a linear combination of some la...
Balanced Incomplete Latin Square Designs
Balanced incomplete Latin square information matrix optimality orthogonal Latin square
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2016/1/25
Latin squares have been widely used to design an experiment where the blocking factors and treatment factors are of the same levels. For some experiments, the size of blocks may be less than the numbe...
Vanilla Lasso for sparse classification under single index models
Vanilla Lasso sparse classification single index models
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2016/1/20
This paper study sparse classification problems. We show that under single-index models, vanilla Lasso could give good estimate of unknown parameters. With this result, we see that even if the model i...
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
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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...
Spatial Panel Data Models. Oxford Handbook of Panel Data
Spatial Panel Data Models Oxford Handbook Panel Data
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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...
Identification of spatial panel Durbin models
Spatial autoregression Durbin regressors Spatial VAR Dynamic panel Fixed e¤ects Random e¤ects
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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
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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...
Joint Modeling and Clustering Paired Generalized Longitudinal Trajectories with Application to Cocaine Abuse Treatment Data
Clustering functional data analysis exponential family joint modeling EM algorithm
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2016/1/20
In a cocaine dependence treatment study, we have paired binary longitudinal tra-jectories that record the cocaine use patterns of each patient before and after a treat-ment. To better understand the d...
Central Limit Theorems for Supercritical Branching Nonsymmetric Markov Processes
Central limit theorem branching Markov process supercritical mar- tingale
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2016/1/20
In this paper, we establish a spatial central limit theorem for a large class of supercritical branching, not necessarily symmetric, Markov processes with spatially dependent branching mechanisms sati...
Sliced space-filling designs with different levels of two-dimensional uniformity
Asymmetric Balanced Computer experiment Sliced orthogonal array
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2016/1/20
We consider sliced computer experiments where priori knowledge suggests that factors may have different levels of importance, and so some factors need to be paid more attention than others. A new clas...
Varying Naive Bayes Models with Applications toClassi cation of Chinese Text Documents
BIC Chinese Document Classification Screening Consistency Time-dependent Classification Rule
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2016/1/20
Document classification is an area of great importance for which many clas-sification methods have been well developed. However, most of these methods cannot generate time-dependent classification rul...
Concise Comparative Summaries (CCS) of Large Text Corpora with a Human Experiment
text summarization high-dimensional analysis sparse model- ing, Lasso L1 regularized logistic regression co-occurrence tf-idf
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2016/1/20
In this paper, we propose a general framework for topic-specific summarization of large text corpora, and illustrate how it can be used for the analysis of news databases. Our framework, concise compa...