搜索结果: 1-15 共查到“理论统计学 hierarchical”相关记录20条 . 查询时间(0.165 秒)
Learning interactions via hierarchical group-lasso regularization
hierarchical interaction computer intensive regression logistic
2015/8/21
We introduce a method for learning pairwise interactions in a linear regression or logistic regression model in a manner that satisfies strong hierarchy: whenever an interaction is estimated to be non...
Conjugate distributions in hierarchical Bayesian ANOVA for computational efficiency and assessments of both practical and statistical significance
ANOVA xed eects random eects variance components hierar-chical Bayes multilevel model constraints
2013/4/27
Assessing variability according to distinct factors in data is a fundamental technique of statistics. The method commonly regarded to as analysis of variance (ANOVA) is, however, typically confined to...
Classification Loss Function for Parameter Ensembles in Bayesian Hierarchical Models
Classification Loss Function Parameter Ensembles Bayesian Hierarchical Models
2011/6/20
Our perspective in this paper follows the framework adopted by Lin et al. (2006), who intro-
duced several loss functions for the identi cation of the elements of a parameter ensemble that
represent...
Hierarchical structure in phonographic market
Life time of correlation correlation coefficient phonographic market
2011/6/21
I find a topological arrangement of assets traded in a phonographic market
which has associated a meaningful economic taxonomy. I continue using
the Minimal Spanning Tree and the Life-time Of Correl...
Multi-scale Mining of fMRI data with Hierarchical Structured Sparsity
brain reading structured sparsity convex optimization sparse hierarchical models inter-subject validation proximal methods
2011/6/16
Inverse inference, or “brain reading”, is a recent paradigm for analyzing functional magnetic resonance imaging (fMRI) data, based on pattern recognition and statistical learning. By predicting some c...
Methods of Hierarchical Clustering
Hierarchical Clustering hierarchical grid-based algorithm hierarchical density-based approaches
2011/6/20
We survey agglomerative hierarchical clustering algorithms and dis-
cuss efficient implementations that are available in R and other software
environments. We look at hierarchical self-organizing ma...
Active Clustering: Robust and Efficient Hierarchical Clustering using Adaptively Selected Similarities
Active Clustering Robust and Efficient Hierarchical Clustering Adaptively Selected Similarities
2011/3/25
Hierarchical clustering based on pairwise similarities is a common tool used in a broad range of scientific applications. However, in many problems it may be expensive to obtain or compute similaritie...
A Bayesian Hierarchical Modeling Approach to Dietary Assessment via Food Frequency
Bayesian Hierarchical Modeling Approach Dietary Assessment Food Frequency
2010/4/26
Previous likelihood-based linear modeling of nutritional data has been limited by the availability of software that allows flexible error structures in the data. We demonstrate the use of a Bayesian m...
Inference in HIV dynamics models via hierarchical likelihood
algorithm asymptotic di erential equations h-likelihood HIV dynamics models non-linear mixed e ects model penalized likelihood.
2010/3/10
HIV dynamical models are often based on non-linear systems
of ordinary di erential equations (ODE), which do not have analytical
solution. Introducing random e ects in such models leads to very chal...
Hierarchical Model Building, Fitting, and Checking: A Behind-the-Scenes Look at a Bayesian Analysis of Arsenic Exposure Pathways
Bayesian learning data management environmental health model validation
2009/9/24
In this article,we present a behind-the-scenes look at a Bayesian
hierarchical analysis of pathways of exposure to arsenic(a toxic heavy metal)
using the Phase I National Human Exposure Assessment ...
Bayesian Diagnostic Techniques for Detecting Hierarchical Structure
model assessment partial posterior predictive p value posterior predictive distribution posterior predictive p value
2009/9/22
Motivated by an increasing number of Bayesian hierarchical model
applications, the objective of this paper is to evaluate properties of several di-
agnostic techniques when the tted model includes s...
Bayesian Hierarchical Multiresolution Hazard Model for the Study of Time-Dependent Failure Patterns in Early Stage Breast Cancer
Multiresolution models Bayesian survival analysis hazard estimation
2009/9/22
In this paper, we extend the previously proposed MRH methods(Bouman et al.2005, 2007) into the hierarchical multiresolution hazard setting (HMRH), to accommodate the case of separate hazard rate funct...
Identifying outliers in Bayesian hierarchical models: a simulation-based approach
Hierarchical models diagnostics outliers distributional assumptions
2009/9/22
A variety of simulation-based techniques have been proposed for detec-
tion of divergent behaviour at each level of a hierarchical model. We investigate a
diagnostic test based on measuring the coni...
Loss Function Based Ranking in Two-Stage, Hierarchical Models
percentiling Bayesian models decision theory operating characteristic
2009/9/21
Performance evaluations of health services providers burgeons. Simi-
larly, analyzing spatially related health information, ranking teachers and schools,
and identification of differentially express...
The Relationship Between the Power Prior and Hierarchical Models
Generalized linear model hierarchical model historical data power prior prior elicitation random eects model
2009/9/21
The power prior has emerged as a useful informative prior for the incorpora-
tion of historical data in a Bayesian analysis. Viewing hierarchical modeling as
the gol standard for combining informati...