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Testing in the Presence of Nuisance Parameters: Some Comments on Tests Post-Model-Selection and Random Critical Values
Nuisance Parameters Post-Model-Selection Random Critical Values
2012/11/22
We point out that the ideas underlying some test procedures recently proposed for testing post-model-selection (and for some other test problems) in the econometrics literature have been around for qu...
Selection of Identifiability Criteria for Total Effects by using Path Diagrams
Selection Identifiability Criteria Total Effects Path Diagrams
2012/9/19
Pearl has provided the back door criterion,the front door criterion and the conditional instrumental variable (IV) method as iden-tifiability criteria for total effects.In some situations,these three ...
Unified Analysis of Transmit Antenna Selection/Space-Time Block Coding with Receive Selection and Combining over Nakagami-m Fading Channels in the Presence of Feedback Errors
Space-Time Block Coding (STBC) Transmit Antenna Selection (TAS) Receive Antenna Selection (RAS) Maximal-ratio Combining (MRC) Selection Combining (SC) Nakagami-m fading Feedback Errors
2012/9/18
Examining the effect of imperfect transmit antenna selection (TAS) caused by the feedback link errors on the performance of hybrid TAS/space-time block co ding (STBC) with selection combining (SC) (i....
Variable Selection with Exponential Weights and $l_0$-Penalization
Variable selection model selection sparse linear model xponential weights Gibbs sampler identifiability condition.
2012/9/17
In the context of a linear model with a sparse coefficient vector, exponential weights methods have been shown to be achieve oracle inequalities for prediction. We show that such methods also succeed ...
Simultaneous Model Selection and Estimation for Mean and Association Structures with Clustered Binary Data
association clustered binary data generalized estimating equation logistic regression variable selection
2012/9/17
This paper investigates the property of the penalized estimating equations when both the mean and association structures are modelled. To select variables for the mean and association structures seque...
The Dependence of Routine Bayesian Model Selection Methods on Irrelevant Alternatives
Bayesian Model Selection Methods Alternatives
2012/9/17
Bayesian methods - either based on Bayes Factors or BIC - are now widely used for model selection. One property that might reasonably be demanded of any model
selection method is that if a modelM1 is...
Consistent selection of tuning parameters via variable selection stability
kappa coefficient penalized regression selection consistency stability tuning
2012/9/17
Penalized regression models are popularly used in high-dimensional data analysis to conduct variable selection and model fitting simultaneously. Whereas success has been widely reported in literature,...
Oracle inequalities for computationally adaptive model selection
Oracle computationally adaptive model selection
2012/9/17
We analyze general model selection procedures using penalized empirical loss minimization under computational constraints. While classical model selection approaches do not consider computational aspe...
Gaussian Oracle Inequalities for Structured Selection in Non-Parametric Cox Model
Gaussian Oracle Inequalities Structured Selection Non-Parametric Cox Model
2012/9/19
To better understand the interplay of censoring and sparsity we develop finite sample properties of nonparametric Cox proportional hazard乫s model. Due to high impact of sequencing data, carrying genet...
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.