搜索结果: 1-15 共查到“统计学其他学科 Inference”相关记录21条 . 查询时间(0.078 秒)
Statistical inference in compound functional models
Compound functional model minimax estimation sparse additive structure dimen-sion reduction structure adaptation
2012/9/18
We consider a general nonparametric regression model called the compound model. It includes,as special cases, sparse additive regression and nonparametric (or linear) regression with many covariates b...
Geometry of faithfulness assumption in causal inference
causal inference PC-algorithm (strong) faithfulness conditional independence directed acyclic graph structural equation model real algebraic hypersurface Crofton's formula algebraic statistics.
2012/9/18
Many algorithms for inferring causality rely heavily on the faithfulness assumption.The main justi cation for imposing this assumption is that the set of unfaithful distribu-tions has Lebesgue measure...
Statistical Inference of Allopolyploid Species Networks in the Presence of Incomplete Lineage Sorting
Allopolyploid hybridization Bayesian phylogenetics network
2012/9/18
Polyploidy is an important speciation mechanism, particularly in land plants. Allopolyploid species are formed after hybridization betweenother-wise intersterile parental species. Recent theoretical p...
Nonparametric Inference for Max-Stable Dependence
Nonparametric Inference Max-Stable Dependence
2012/9/17
The choice for parametric techniques in the dis-cussion article is motivated by the claim that for multivariate extreme-value distributions, “owing to
the curse of dimensionality, nonparametric estim...
Inference of time-varying regression models
Information criterion locally stationary processes nonpara-metric hypothesis testings time-varying coefficient models variable selection.
2012/9/17
We consider parameter estimation, hypothesis testing and vari-able selection for partially time-varying coefficient models. Our asymp-totic theory has the useful feature that it can allow dependent, n...
Bayesian inference on dependence in multivariate longitudinal data
Cholesky decomposition covariance matrix moment-matching oxidative stress random effects shrinkage prior.
2012/9/17
In many applications, it is of interest to assess the dependence structure in multivariate longitudinal data. Discovering such dependence is challenging
due to the dimensionality involved. By concate...
Massive parallelization of serial inference algorithms for a complex generalized linear model
Massive parallelization serial inference algorithms generalized linear model
2012/9/17
Following a series of high-pro le drug safety disasters in recent years, many countries are redoubling their e orts to ensure the safety of licensed medical products. Large-scale observa-tional databa...
Ancestral Inference from Functional Data: Statistical Methods and Numerical Examples
comparative analysis Ornstein-Uhlenbeck process non-parametric Bayesian infer-ence functional phylogenetics ancestral reoncon-struction
2012/9/17
Many biological characteristics of evolutionary inter-est are not scalar variables but continuous functions.Here we use phylogenetic Gaussian process regres-sion to model the evolution of simulated fu...
Causal Inference on Time Series using Structural Equation Models
Causal Inference Time Series Structural Equation Models
2012/9/19
Causal inference uses observations to infer the causal structure of the data generating system.We study a class of functional models that we call Time Series Models with Independent Noise (TiMINo). Th...
Robust Bayesian inference of networks using Dirichlet t-distributions
Bayesian inference Dirichlet process graphical model Markov chain Monte Carlo t-distribution.
2012/9/18
Bayesian graphical modeling provides an appealing way to obtain uncertainty esti-mates when inferring network structures, and much recent progress has been made for Gaussian models. These models have ...
Discussion of "Statistical Inference: The Big Picture" by R. E. Kass
Discussion Statistical Inference The Big Picture R. E. Kass
2011/7/6
Rob Kass presents a fascinating vision of a “post”-Bayes/frequentist-controversy world in which prac-tical utility of statistical models is the guiding prin-ciple for statistical inference.
Discussion of "Statistical Inference: The Big Picture" by R. E. Kass
Discussion Statistical Inference Big Picture R. E. Kass
2011/7/5
Kass states (page 5) that Figure 3 is not a good general description of statistical inference and that Figure 1 is more accurate. I completely agree. Kass states (page 5) that “It is important for stu...
Semiparametric inference in mixture models with predictive recursion marginal likelihood
Density estimation Dirichlet process mixture empirical Bayes filtering algorithm
2011/7/5
Predictive recursion is an accurate and computationally efficient algorithm for nonparametric estimation of mixing densities in mixture models. In semiparametric mixture models, however, the algorithm...
Fast Inference of Interactions in Assemblies of Stochastic Integrate-and-Fire Neurons from Spike Recordings
Bayesian procedures noise variance activity of the salamander
2011/3/24
We present two Bayesian procedures to infer the interactions and external currents in an assembly of stochastic integrate-and-fire neurons from the recording of their spiking activity. The first proce...
Causal graphical models in systems genetics: A unified framework for joint inference of causal network and genetic architecture for correlated phenotypes
Causal graphical models QTL mapping joint inference of phenotype network and genetic architecture systems genetics
2010/10/19
Causal inference approaches in systems genetics exploit quantitative trait loci (QTL) genotypes to infer causal relationships among phenotypes. The genetic architecture of each phenotype may be comple...