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厦门大学经济学院统计系博士生范新妍论文被Journal of Multivariate Analysis正式接收（图）
厦门大学经济学院 统计系 博士生 范新妍论文 Journal of Multivariate Analysis
2018/2/3
近日，由我校经济学院统计系2015级在读博士生范新妍与其导师组成员方匡南教授、张庆昭副教授、美国耶鲁大学马双鸽教授合作完成的论文“Integrative sparse principal component analysis of multiple heterogeneous datasets”被Journal of Multivariate Analysis正式接收，即将刊出。Journal o...
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...
Multivariate Standardized Time Series for Steady-State Simulation Output Analysis
Simulation statistical analysis multivariate steady-state output analysi
2015/7/8
The theory of standardized time series, initially proposed to estimate a single steady-state mean from the output of a simulation, is extended to the case where more than one steady-state mean is to b...
Resources, Capabilities, and the Performance of Industrial Firms: A Multivariate Analysis
Resources Capabilities the Performance of Industrial Firms A Multivariate Analysis
2015/1/26
Much effort has been directed in the last decade to the theoretical foundations of the resource-based view (RBV) of strategic management. However, this approach has been criticized and its standing as...
Topics in Multivariate Time Series Analysis: Statistical Control, Dimension Reduction Visualization and Thir Business Applications
Topics in Multivariate Time Series Analysis Statistical Control Dimension Reduction Visualization Their Business Applications
2014/10/28
Most business processes are, by nature, multivariate and autocorrelated. Highdimensionality is rooted in processes where more than one variable is considered simultaneously to provide a more comprehen...
A simple proof for the multivariate Chebyshev inequality
Chebyshev (Tchebychev) inequality Mahalanobis distance Principal compo-nents Ellipsoid
2013/6/14
In this paper a simple proof of the Chebyshev's inequality for random vectors obtained by Chen (arXiv:0707.0805v2, 2011) is obtained. This inequality gives a lower bound for the percentage of the popu...
A Semiparametric Estimator for Long-Range Dependent Multivariate Processes
Multivariate processes Long-range dependence Semiparametric estimation VARFIMA processes Asymptotic theory
2013/6/14
In this paper we propose a generalization of a class of Gaussian Semiparametric Estimators (GSE) of the fractional differencing parameter for long-range dependent multivariate time series. We generali...
Simple Le Cam optimal inference for the tail weight of multivariate Student $t$ distributions: testing procedures and estimation
local asymptotic normality locally asymptotically maximin tests one-step estimation Student t distribution tail weight
2013/6/14
The multivariate Student $t$ distribution is at the core of classical statistical inference and is also a well-known model for empirical financial data. In the present paper, we propose optimal (in th...
Efficient Algorithms for Multivariate Linear Mixed Models in Genome-wide Association Studies
Efficient Algorithms Multivariate Linear Mixed Models Genome-wide Association Studies
2013/6/17
Multivariate linear mixed models (mvLMMs) have been widely used in many areas of genetics, and have attracted considerable recent interest in genome-wide association studies (GWASs). However, existing...
Dynamic Covariance Models for Multivariate Financial Time Series
Dynamic Covariance Models Multivariate Financial Time Series
2013/6/14
The accurate prediction of time-changing covariances is an important problem in the modeling of multivariate financial data. However, some of the most popular models suffer from a) overfitting problem...
Ensemble Copula Coupling as a Multivariate Discrete Copula Approach
multivariate discrete copula stochastic array Sklar’s theorem statistical ensemble postprocessing ensemble copula coupling
2013/6/14
In probability and statistics, copulas play important roles theoretically as well as to address a wide range of problems in various application areas. In this paper, we introduce the concept of multiv...
We propose a new method named calibrated multivariate regression (CMR) for fitting high dimensional multivariate regression models. Compared to existing methods, CMR calibrates the regularization for ...
A least-squares method for sparse low rank approximation of multivariate functions
least-squares method sparse low rank approximation multivariate functions
2013/6/14
In this paper, we propose a low-rank approximation method based on discrete least-squares for the approximation of a multivariate function from random, noisy-free observations. Sparsity inducing regul...
A closed-form estimator for the multivariate GARCH(1,1) model
Multivariate GARCH(1,1) VARMA Temporal Aggregation Es-timation
2013/4/27
We provide a closed-form estimator based on the VARMA representation for the unrestricted multivariate GARCH(1,1). We show that all parameters can be derived using basic linear algebra tools. We show ...
We define and study a generalization of Sobol sensitivity indices for the case of a vector output.