搜索结果: 1-15 共查到“统计学 G-computation”相关记录22条 . 查询时间(0.125 秒)
Geometric stabilization of extended S=2 vortices in two-dimensional photonic lattices: Theoretical analysis, numerical computation, and experimental results
Nonlinear discrete nearly two-dimensional photonic crystal lattice whirlpool discrete vortex model
2014/12/24
In this work, we focus on the subject of nonlinear discrete self-trapping of S=2 (doubly-charged) vortices in two-dimensional photonic lattices, including theoretical analysis, numerical computation, ...
Discrete Breathers in a Forced-Damped Array of Coupled Pendula: Modeling, Computation, and Experiment
Machinery the localization model enhance the liquidity local mode damping coupling
2014/12/24
In this work, we present a mechanical example of an experimental realization of a stability reversal between on-site and intersite centered localized modes. A corresponding realization of a vanishing ...
Bayesian Modeling and MCMC Computation in Linear Logistic Regression for Presence-only Data
Bayesian modeling case-control design data augmentation logistic regres-sion Markov Chain Monte Carlo population prevalence presence-only data simulation
2013/6/13
Presence-only data are referred to situations in which, given a censoring mechanism, a binary response can be observed only with respect to on outcome, usually called \textit{presence}. In this work w...
On computation of clustering coefficient in a class of random networks
random graph clustering degree of separation
2012/9/18
The random networks enriched with additional structures asmetric and group-symmetry in background metric space are investigated. The important quantities like he clustering coefficient as well as the ...
Mixing Coefficients Between Discrete and Real Random Variables: Computation and Properties
Mixing Coefficients Between Discrete Real Random Variables Computation Properties
2012/9/17
In this paper we study the problem of estimating the mixing coefficients between two random vari-ables. Three different mixing coefficients are studied,namely alpha-mixing, beta-mixing and phi-mixing ...
Efficient computation with a linear mixed model on large-scale data sets with applications to genetic studies
Efficient computation a linear mixed model on large-scale data sets applications genetic studies
2012/9/19
Motivated by genome-wide association studies we consider astan-dard linear model with one additional random effect in situations where many predictors have been collected on the same subjects and each...
abc: an R package for Approximate Bayesian Computation (ABC)
abc package Approximate Bayesian Computation
2011/7/7
Many recent statistical applications involve inference under complex models, where it is computationally prohibitive to calculate likelihoods but possible to simulate data.
The AEP algorithm for the fast computation of the distribution of the sum of dependent random variables
convolution istribution functions
2011/7/5
We propose a new algorithm to compute numerically the distribution function of the sum of $d$ dependent, non-negative random variables with given joint distribution.
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...
Using parallel computation to improve Independent Metropolis--Hastings based estimation
MCMC algorithm independent Metropolis{Hastings
2010/10/19
In this paper, we consider the implications of the fact that parallel raw-power can be exploited by a generic Metropolis--Hastings algorithm if the proposed values are independent. In particular, we p...
Implementing regularization implicitly via approximate eigenvector computation
Implementing regularization implicitly via approximate eigenvector computation
2010/10/19
Regularization is a powerful technique for extracting useful information from noisy data. Typically, it is implemented by adding some sort of norm constraint to an objective function and then exactly...
Measures of Analysis of Time Series (MATS):A MATLAB Toolkit for Computation of Multiple Measures on Time Series Data Bases
time series analysis data bases nonlinear dynamics statistical measures MATLAB software changedetection surrogate data
2010/3/10
In many applications, such as physiology and finance, large time series data bases are to be analyzed requiring
the computation of linear, nonlinear and other measures. Such measures have been develo...
On sequential Monte Carlo，partial rejection control and approximate Bayesian computation
Approximate Bayesian computation Bayesian computation Likelihood free inference Sequential Monte Carlo samplers
2010/4/30
We present a sequential Monte Carlo sampler variant of the partial rejection
control algorithm, and show that this variant can be considered as a sequential
Monte Carlo sampler with a modified mutat...
Bayesian Variable Selection and Computation for Generalized Linear Models with Conjugate Priors
Bayes factor Conditional Predictive Ordinate Conjugate prior Poisson regression Logistic regression
2009/9/22
In this paper, we consider theoretical and computational connections
between six popular methods for variable subset selection in generalized linear
models (GLMs) Under the conjugate priors develope...
Nested Sampling for General Bayesian Computation
Bayesian computation evidence marginal likelihood algorithm nest annealing phase change model selection
2009/9/21
Nested sampling estimates directly how the likelihood function relates
to prior mass. The evidence (alternatively the marginal likelihood, marginal den-
sity of the data, or the prior predictive) is...