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Enterprise risk management: a DEA VaR approach in vendor selection
data envelopment analysis (DEA) enterprise risk management supply chains
2011/10/8
Enterprise risk management (ERM) has become an important topic in today's more complex, interrelated global business environment, replete with threats from natural, political, economic, and technical ...
The Impact of Technology Selection on Innovation Success and Organizational Performance
Technology Selection Technological Capability Technology Management Capability Innovation Success Organizational Performance
2013/2/23
This paper is to analyze the impact of a company’s technology selection on its innovation success and organizational performance. Technological capability enables a company to add value to products an...
Sequential Lasso for feature selection with ultra-high dimensional feature space
extended BIC feature selection selection consistency Sequential Lasso
2011/7/19
We propose a novel approach, Sequential Lasso, for feature selection in linear regression models with ultra-high dimensional feature spaces.
Application of Predictive Model Selection to Coupled Models
Predictive Model Selection Quantity of In-terest Model Validation Decision Making
2011/7/19
A predictive Bayesian model selection approach is presented to discriminate coupled models used to predict an unobserved quantity of interest (QoI).
Model selection by LASSO methods in a change-point model
change-points selection criterion asymptotic behavior
2011/7/19
The paper considers a linear regression model with multiple change-points occurring at unknown times.
Co-evolution of Selection and Influence in Social Networks
Co-evolution Selection Influence Social Networks
2011/7/7
Many networks are complex dynamical systems, where both attributes of nodes and topology of the network (link structure) can change with time. We propose a model of co-evolving networks where both nod...
Considerate Approaches to Achieving Sufficiency for ABC model selection
Considerate Approaches Achieving Sufficiency ABC model selection
2011/7/6
For nearly any challenging scientific problem evaluation of the likelihood is problematic if not impossible. Approximate Bayesian computation (ABC) allows us to employ the whole Bayesian formalism to ...
Grouped Variable Selection via Nested Spike and Slab Priors
Log-sum approximation Majorization-minimization algorithms
2011/7/6
In this paper we study grouped variable selection problems by proposing a specified prior, called the nested spike and slab prior, to model collective behavior of regression coefficients.
Tight conditions for consistency of variable selection in the context of high dimensionality
variable selection nonparametric regression set estimation sparsity pattern
2011/7/6
We address the issue of variable selection in the regression model with very high ambient dimension, i.e., when the number of variables is very large. The main focus is on the situation where the numb...
Adjusting for selection bias in testing multiple families of hypotheses
false discovery rate family-wise error rate hierarchical testing
2011/7/6
In many large multiple testing problems the hypotheses are divided into families. Given the data, families with evidence for true discoveries are selected, and hypotheses within them are tested.
Multiple Hypotheses Testing For Variable Selection
model selection FDR Lasso Bolasso multiple hypotheses testing
2011/7/6
Many methods have been developed to estimate the set of relevant variables in a sparse linear model Y= XB+e where the dimension p of B can be much higher than the length n of Y.
Variable Selection for Nonparametric Gaussian Process Priors: Models and Computational Strategies
Bayesian variable selection generalized linear models Gaussian processes
2011/7/5
This paper presents a unified treatment of Gaussian process models that extends to data from the exponential dispersion family and to survival data.
spikeSlabGAM: Bayesian Variable Selection, Model Choice and Regularization for Generalized Additive Mixed Models in R
MCMC P-splines spike-and-slab prior normal-inverse-gamma
2011/6/20
The R package spikeSlabGAM implements Bayesian variable selection, model choice,
and regularized estimation in (geo-)additive mixed models for Gaussian, binomial, and
Poisson responses. Its purpose ...
Variable selection with error control: Another look at Stability Selection
Complementary Pairs Stability Selection r-concavity subagging subsampling variable selection
2011/6/20
Stability Selection was recently introduced by Meinshausen and B¨uhlmann (2010) as
a very general technique designed to improve the performance of a variable selection
algorithm. It is based on aggr...
Consistent Model Selection of Discrete Bayesian Networks from Incomplete Data
Discrete Bayesian Networks Consistent Model Incomplete Data node-variables
2011/6/20
A maximum likelihood based model selection of discrete Bayesian
networks is considered. The model selection is performed through scoring
function S, which, for a given network G and n-sample Dn, is ...