搜索结果: 31-45 共查到“理论统计学 Sampling”相关记录50条 . 查询时间(0.092 秒)
Importance Re-sampling MCMC for Cross-Validation in Inverse Problems
Cross-validation Inverse Importance Re-sampling Model fit Re-use
2009/9/22
This paper presents a methodology for cross-validation in the context of Bayesian
modelling of situations we loosely refer to as iverse problems It is motivated by
an example from palaeoclimatology ...
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...
A note on impotance sampling simulation for germ-grain model
Germ-gain model Poisson process change of measure likelihood process stopping set
2009/9/21
In this paper we demonstrate how to use the importance
sampling method to simulate rare wmts in a germ-grain model. We
analyze conditions under which two gerrn-grain models are mutually
absolutely ...
Improvement on Estimating Current Population Ratio in Successive Sampling
Estimating Current Population Ratio Successive Sampling
2009/9/17
Improvement on Estimating Current Population Ratio in Successive Sampling。
On a πps Scheme of Sampling of Two Units。
How to Combine Fast Heuristic Markov Chain Monte Carlo with Slow Exact Sampling
Confidence interval Exact sampling Markov Chain Monte Carlo
2009/5/4
Given a probability law $pi$ on a set S and a function $g : S rightarrow R$, suppose one wants to estimate the mean $bar{g} = int g dpi$. The Markov Chain Monte Carlo method consists of inventing and ...
Equidistant sampling for the maximum of a Brownian motion with drift on a finite horizon
Gaussian random walk maximum Riemann zeta function Euler-Maclaurin summation equidistant sampling of Brownian motion finite horizon
2009/4/29
A Brownian motion observed at equidistant sampling points renders a random walk with normally distributed increments. For the difference between the expected maximum of the Brownian mo- tion and its s...
Sampling Formulae for Symmetric Selection
Ewens sampling formula partition structure symmetric selection homozygosity
2009/4/27
We study partition distributions in a population genetics model incorporating symmetric selection and mutation. They generalize Ewens distributions in the infinitely-many-neutral-alleles model, an exp...
Equidistant sampling for the maximum of a Brownian motion with drift on a finite horizon
Brownian motion finite horizon
2009/4/22
A Brownian motion observed at equidistant sampling points renders a random walk with normally distributed increments. For the difference between the expected maximum of the Brownian mo- tion and its s...
Perfect sampling from the limit of deterministic products of stochastic matrices
sampling limit product
2009/3/20
We illustrate how a technique from the theory of random iterations of functions can be used within the theory of products of matrices. Using this technique we give a simple proof of a basic theorem ab...
Estimation of cosmological parameters using adaptive importance sampling
Estimation cosmological parameters adaptive importance sampling
2010/3/19
We present a Bayesian sampling algorithm called adaptive importance sampling or Population
Monte Carlo (PMC), whose computational workload is easily parallelizable and thus has the potential to consi...
A Gibbs Sampling Alternative to Reversible Jump MCMC
Gibbs sampler Model switching Variable dimension
2010/3/18
This note presents a simple and elegant sampler which
could be used as an alternative to the reversible jump MCMC methodology.
Gibbs Sampling，Exponential Families and Orthogonal Polynomials
Gibbs sampler running time analyses exponential families conjugate priors location families orthogonal polynomials
2010/4/30
We give families of examples where sharp rates of convergence
to stationarity of the widely used Gibbs sampler are available.
The examples involve standard exponential families and their conjugate
...
Comment：Gibbs Sampling，Exponential Families and Orthogonal Polynomials
Comment Gibbs Sampling Exponential Families Orthogonal Polynomials
2010/4/30
Let K be a reversible Markov kernel on a measurable
space (S,B) with stationary distribution P.
Regard K as a linear operator, K:L2(P)→L2(P),
and suppose that L2(P) admits an orthonormal basis
of ...
Comment：Lancaster Probabilities and Gibbs Sampling
Comment Lancaster Probabilities Gibbs Sampling
2010/4/30
It is a pleasure to congratulate the authors for
this excellent, original and pedagogical paper. I read
a preliminary draft at the end of 2006 and I then
mentioned to the authors that their work sh...