搜索结果: 1-15 共查到“理论统计学 Model Selection”相关记录24条 . 查询时间(0.046 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...
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...
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).
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 ...
The goal of cross-domain object matching (CDOM) is to find correspondence between two sets of objects in different domains in an unsupervised way. Photo album summarization is a typical application of...
Model Selection by Loss Rank for Classification and Unsupervised Learning
Classification graphical models loss rank principle model selection
2010/11/9
Hutter (2007) recently introduced the loss rank principle (LoRP) as a general-purpose principle for model selection. The LoRP enjoys many attractive prop-erties and deserves further investigations. Th...
High-dimensional Ising model selection using ${\ell_1}$-regularized logistic regression
High-dimensional model selection
2010/10/14
We consider the problem of estimating the graph associated with a binary Ising Markov random field. We describe a method based on $\ell_1$-regularized logistic regression, in which the neighborhood of...
High-dimensional Gaussian model selection on a Gaussian design
High-dimensional Gaussian model selection Gaussian design
2010/4/30
High-dimensional Gaussian model selection on a Gaussian design。
Gaussian model selection with an unknown variance
Model selection penalized criterion AIC FPE BIC AMDL variable selection change-points detection adaptive estimation
2010/4/26
Let Y be a Gaussian vector whose components are independent
with a common unknown variance. We consider the problem of estimating
the mean μ of Y by model selection. More precisely, we start
with a...
Reconciling Model Selection and Prediction
AIC BIC Consistency Contiguity Local alternative Minimax-rate optimality
2010/3/18
It is known that there is a dichotomy in the performance of model selectors.
Those that are consistent (having the “oracle property”) do not achieve the
asymptotic minimax rate for prediction error....
Bayesian Computation and Model Selection in Population Genetics
Bayesian Computation Model Selection Population Genetics
2010/3/17
Until recently, the use of Bayesian inference in population genetics was lim-
ited to a few cases because for many realistic population genetic models the
likelihood function cannot be calculated an...
Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems
Approximate Bayesian computation scheme parameter inference model selection dynamical systems
2010/3/17
Approximate Bayesian computation methods can be used to evaluate posterior distributions without having to calculate likelihoods. In this paper we discuss and apply an approximate Bayesian computation...