搜索结果: 1-15 共查到“理论统计学 G-computation”相关记录15条 . 查询时间(0.265 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...
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...
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...
Exact Computation of Minimum Sample size for Estimation of Poisson Parameters
Exact Computation Minimum Sample size Estimation Poisson Parameters
2010/4/30
In this paper, we develop an approach for the exact determination of the minimum sample
size for the estimation of a Poisson parameter with prescribed margin of error and confidence
level. The exact...
Exact Computation of Minimum Sample Size for Estimation of Binomial Parameters
Exact Computation Minimum Sample Size Estimation Binomial Parameters
2010/4/30
It is a common contention that it is an “impossible mission” to exactly determine the
minimum sample size for the estimation of a binomial parameter with prescribed margin of
error and confidence le...
Exact Computation of Minimum Sample Size for Estimating Proportion of Finite Population
Exact Computation Minimum Sample Size Estimating Proportion Finite Population
2010/4/30
In this paper, we develop an exact method for the determination of the minimum sample
size for estimating the proportion of a finite population with prescribed margin of error and
confidence level. ...
Fast computation by block permanents of cumulative distribution functions of order statistics from several populations
block matrix computational complexity multiple comparison
2010/4/29
The joint cumulative distribution function for order statistics arising
from several different populations is given in terms of the distribution
function of the populations. The computational cost o...
Computation of Power Loss in Likelihood Ratio Tests for Probability Densities Extended by Lehmann Alternatives
Computation Power Loss Likelihood Ratio Tests Probability Densities Lehmann Alternatives
2010/4/27
We compute the loss of power in likelihood ratio tests when we test
the original parameter of a probability density extended by the first
Lehmann alternative.