搜索结果: 1-15 共查到“统计学 Model Selection”相关记录46条 . 查询时间(0.115 秒)
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...
Model Selection for High-Dimensional Regression under the Generalized Irrepresentability Condition
Model Selection High-Dimensional Regression Generalized Irrepresentability Condition
2013/6/13
In the high-dimensional regression model a response variable is linearly related to $p$ covariates, but the sample size $n$ is smaller than $p$. We assume that only a small subset of covariates is `ac...
Group-Sparse Model Selection: Hardness and Relaxations
Signal Approximation Structured Sparsity Interpretability Tractability Dynamic Programming Compressive Sensing
2013/5/2
Group-based sparsity models are proven instrumental in linear regression problems for recovering signals from much fewer measurements than standard compressive sensing. The main promise of these model...
Model selection and clustering in stochastic block models with the exact integrated complete data likelihood
Random graphs stochastic block models integrated classication likelihood
2013/4/27
The stochastic block model (SBM) is a mixture model used for the clustering of nodes in networks. It has now been employed for more than a decade to analyze very different types of networks in many sc...
Model selection and estimation of a component in additive regression
Model selection estimation component additive regression
2012/11/23
Let $Y\in\R^n$ be a random vector with mean $s$ and covariance matrix $\sigma^2P_n\tra{P_n}$ where $P_n$ is some known $n\times n$-matrix. We construct a statistical procedure to estimate $s$ as well ...
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...
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...
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...
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.
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 ...
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 ...
Deviance Information Criteria for Model Selection in Approximate Bayesian Computation
Approximate Bayesian computation evolutionary genetics statistical
2011/6/16
Approximate Bayesian computation (ABC) is a class of algorithmic
methods in Bayesian inference using statistical summaries and computer
simulations. ABC has become popular in evolutionary genetics a...
Estimating composite functions by model selection
Curve estimation model selection composite functions
2011/3/21
We consider the problem of estimating a function $s$ on $[-1,1]^{k}$ for large values of $k$ by looking for some best approximation by composite functions of the form $g\circ u$. Our solution is based...