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Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：How to capture tourists' search behavior in tourism forecasts？A two-stage feature selection approach
旅游预测 游客 搜索行为 两阶段 特征选择方法
2023/5/16
Search engine data have been widely used and shown to be useful in tourism demand forecasting. However, considering of the vast amounts of search keywords, how to better capture the tourists' attentio...
Genomic response to natural selection within alpine cattle breeds
cattle fitness footprints of selection genomics local adaptation PCAdapt
2018/11/23
The aim of this study was to analyse the genomic regions that have been target of natural selection with respect to identifying the loci responsible mainly for fitness traits across six alpine cattle ...
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...
Band Width Selection for High Dimensional Covariance Matrix Estimation
Bandable covariance Banding estimator Large p, small n Ratio- consistency Tapering estimator Thresholding estimator
2016/1/25
The banding estimator of Bickel and Levina (2008a) and its tapering version of Cai, Zhang and Zhou (2010), are important high dimensional covariance esti-mators. Both estimators require choosing a ban...
Multivariate Regression Shrinkage and Selection by Canonical Correlation Analysis
Adaptive Lasso Canonical Correlation Analysis Multivariate Regression
2016/1/25
The problem of regression shrinkage and selection for multivariate regression is considered. The goal is to consistently identify those variables relevant for regression. This is done not only for pre...
Spatial Weights Matrix Selection and Model Averaging for Spatial Autoregressive Models
Model Selection Model Averaging Spatial Econometrics Spatial Autoregressive
2016/1/20
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...
Band Width Selection for High Dimensional Covariance Matrix Estimation
Bandable covariance Banding estimator Large p small n
2016/1/20
The banding estimator of Bickel and Levina (2008a) and its tapering version of Cai, Zhang and Zhou (2010), are important high dimensional covariance esti-mators. Both estimators require choosing a ban...
On BIC's Selection Consistency for Discriminant Analysis
BIC Discriminant Analysis Selection Consistency
2016/1/19
Linear and quadratic discriminant analysis are two very useful classification methods, for which the problem of variable selection is of fundamental impor-tance. To this end, a BIC-type selection crit...
Factor profiling for ultra high dimensional variable selection
Bayesian Information Criterion Factor Profiling Forward Re- gression Maximum Eigenvalue Ratio Criterion Profiled Independent Screening
2016/1/19
We propose here a novel method of factor profiling (FP) for ultra high dimen-sional variable selection. The new method assumes that the correlation structure of the high dimensional data can be well r...
A Bayesian Information Criterion for Portfolio Selection
Bayesian Information Criterion Minimal Variance Portfolio Portfolio Selection Risk Diversification Selection Consistency
2016/1/19
The mean-variance theory of Markowitz (1952) indicates that large invest-ment portfolios naturally provide better risk diversification than small ones.However, due to parameter estimation errors, one ...
Metric Selection in Fast Dual Forward Backward Splitting
Metric Selection Fast Dual Forward Backward Splitting
2015/7/9
The performance of fast forward-backward splitting, or equivalently fast proximal gradient methods, is susceptible to conditioning of the optimization problem data. This conditioning is related to a m...
On model selection consistency of M-estimators with geometrically decomposable penalties
model selection consistency M-estimators geometrically decomposable penalties
2013/6/14
Penalized M-estimators are used in many areas of science and engineering to fit models with some low-dimensional structure in high-dimensional settings. In many problems arising in bioinformatics, sig...
Supplementary Appendix for "Inference on Treatment Effects After Selection Amongst High-Dimensional Controls"
Supplementary Appendix "Inference on Treatment Effects After Selection Amongst High-Dimensional Controls"
2013/6/14
In this supplementary appendix we provide additional results, omitted proofs and extensive simulations that complement the analysis of the main text
Variable selection for sparse Dirichlet-multinomial regression with an application to microbiome data analysis
Coordinate descent counts data overdispersion regularized likelihood sparse group penalty
2013/6/14
With the development of next generation sequencing technology, researchers have now been able to study the microbiome composition using direct sequencing, whose output are bacterial taxa counts for ea...
Variable selection for sparse Dirichlet-multinomial regression with an application to microbiome data analysis
Coordinate descent counts data overdispersion regularized likelihood sparse group penalty
2013/6/14
With the development of next generation sequencing technology, researchers have now been able to study the microbiome composition using direct sequencing, whose output are bacterial taxa counts for ea...