搜索结果: 106-120 共查到“统计逻辑学”相关记录170条 . 查询时间(0.437 秒)
Penalized Likelihood and Bayesian Function Selection in Regression Models
generalized additive model regularization smoothing spike and slab priors
2013/4/27
Challenging research in various fields has driven a wide range of methodological advances in variable selection for regression models with high-dimensional predictors. In comparison, selection of nonl...
Supplement to "Reversible MCMC on Markov equivalence classes of sparse directed acyclic graphs"
Sparse graphical model Reversible Markov chain Markov equivalence class
2013/4/27
This supplementary material includes three parts: some preliminary results, four examples, an experiment, three new algorithms, and all proofs of the results in the paper "Reversible MCMC on Markov eq...
Top-down particle filtering for Bayesian decision trees
Top-down particle filtering Bayesian decision trees
2013/4/27
Decision tree learning is a popular approach for classification and regression in machine learning and statistics, and Bayesian formulations---which introduce a prior distribution over decision trees,...
Bayesian learning of joint distributions of objects
Bayesian learning joint distributions objects
2013/4/27
There is increasing interest in broad application areas in defining flexible joint models for data having a variety of measurement scales, while also allowing data of complex types, such as functions,...
This paper is a note on the use of Bayesian nonparametric mixture models for continuous time series. We identify a key requirement for such models, and then establish that there is a single type of mo...
Non-identifiability, equivalence classes, and attribute-specific classification in Q-matrix based Cognitive Diagnosis Models
CDM diagnostic classification DINA DINO NIAD-DINA Q-matrix consistency identifiability
2013/4/27
There has been growing interest in recent years in Q-matrix based cognitive diagnosis models. Parameter estimation and respondent classification under these models may suffer due to identifiability is...
A Directional Gradient-Curvature Method for Gap Filling of Gridded Environmental Spatial Data with Potentially Anisotropic Correlations
correlation anisotropy spatial interpolation stochastic estimation optimization simulation
2013/4/27
We introduce the Directional Gradient-Curvature (DGC) method, a novel approach for filling gaps in gridded environmental data. DGC is based on an objective function that measures the distance between ...
近日，浙江大学出版社编制出台《学术著作出版规范》，针对学术著作出版的过程，对书稿的格式、要素、流程和版式等方面提出明确要求。据了解，这是我国出版社出台的第一部学术著作出版规范，将于2012年4月1日起在浙大出版社试行。
Tchebycheff systems and extremal problems for generalized moments: a brief survey
Tchebycheff systems Markov systems extremal problems
2011/7/19
A brief presentation of basics of the theory of Tchebycheff and Markov systems of functions and its applications to extremal problems for integrals of such functions is given.
We study the problem of navigating through a database of similar objects using comparisons. This problem is known to be strongly related to the small-world network design problem.
We consider a basic problem in unsupervised learning: learning an unknown \emph{Poisson Binomial Distribution} over $\{0,1,...,n\}$. A Poisson Binomial Distribution (PBD) is a sum $X = X_1 + ... + X_n...
Topological Randomness and Number of Edges Predict Modular Structure in Functional Brain Networks
Topological Randomness Number Edges Predict Modular Structure Functional Brain Networks
2011/7/7
In a recent paper, Bassett et al. (2011) have analyzed the static and dynamic organization of functional brain networks in humans.
Non-parametric change-point detection using string matching algorithms
School of Mathematics, University of Bristol, University Walk, Bristol, BS8 1TW, UK
2011/7/7
Given the output of a data source taking values in a finite alphabet, we wish to detect change-points, that is times when the statistical properties of the source change.
Learning with the Weighted Trace-norm under Arbitrary Sampling Distributions
Learning Weighted Trace-norm Arbitrary Sampling Distributions
2011/7/7
We provide rigorous guarantees on learning with the weighted trace-norm under arbitrary sampling distributions.
Efficient sampling of high-dimensional Gaussian fields: the non-stationary / non-sparse case
Efficient sampling high-dimensional Gaussian non-stationary non-sparse case
2011/6/20
This paper is devoted to the problem of sampling Gaussian fields
in high dimension. Solutions exist for two specific structures of inverse
covariance : sparse and circulant. The proposed approach is...