搜索结果: 1-15 共查到“理论统计学 Sampling”相关记录50条 . 查询时间(0.196 秒)
Estimating Network Degree Distributions Under Sampling: An Inverse Problem, with Applications to Monitoring Social Media Networks
Estimating Network Degree Distributions Sampling An Inverse Problem Applications Monitoring Social Media Networks
2013/6/14
Networks are a popular tool for representing elements in a system and their interconnectedness. Many observed networks can be viewed as only samples of some true underlying network. Such is frequently...
Penalized importance sampling for parameter estimation in stochastic differential equations
Chronic wasting disease Euler-Maruyama scheme Maximum likelihood estimation Partially observed discrete sparse data Penalized importance sampling Stochastic di
2013/6/14
We consider the problem of estimating parameters of stochastic differential equations with discrete-time observations that are either completely or partially observed. The transition density between t...
Adaptive Metropolis-Hastings Sampling using Reversible Dependent Mixture Proposals
Ergodic convergence Markov Chain Monte Carlo Metropolis-within Gibbs composite sampling Multivariatet mixtures Simulated annealing Variational Approx-imation
2013/6/14
This article develops a general-purpose adaptive sampler that approximates the target density by a mixture of multivariate t densities. The adaptive sampler is based on reversible proposal distributio...
A General Family of Estimators for Estimating Population Mean in Systematic Sampling Using Auxiliary Information in the Presence of Missing Observations
Family of estimators Auxiliary information Mean square error Non-response Systematic sampling
2013/6/14
This paper proposes a general family of estimators for estimating the population mean in systematic sampling in the presence of non-response adapting the family of estimators proposed by Khoshnevisan ...
Central limit theorems for pre-averaging covariance estimators under endogenous sampling times
Central limit theorem Hitting times Market microstructure noise Nonsynchronous observa-tions Pre-averaging Time endogeneity
2013/6/13
We consider two continuous It\^o semimartingales observed with noise and sampled at stopping times in a nonsynchronous manner. In this article we establish a central limit theorem for the pre-averaged...
Generalized Thompson Sampling for Sequential Decision-Making and Causal Inference
Generalized Thompson Sampling Sequential Decision-Making Causal Inference
2013/5/2
Recently, it has been shown how sampling actions from the predictive distribution over the optimal action-sometimes called Thompson sampling-can be applied to solve sequential adaptive control problem...
Variance estimation and asymptotic confidence bands for the mean estimator of sampled functional data with high entropy unequal probability sampling designs
covariance function finite population Hajek approximation Horvitz-Thompso estimator Kullback-Leibler divergence rejective sampling unequal probability sampling without replacement
2012/11/23
For fixed size sampling designs with high entropy it is well known that the variance of the Horvitz-Thompson estimator can be approximated by the H\'ajek formula. The interest of this asymptotic varia...
On Set Size Distribution Estimation and the Characterization of Large Networks via Sampling
On Set Size Distribution Estimation Characterization large Networks via Sampling
2012/11/22
In this work we study the set size distribution estimation problem, where elements are randomly sampled from a collection of non-overlapping sets and we seek to recover the original set size distribut...
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.
Reconstruction of Fractional Brownian Motion Signals From Its Sparse Samples Based on Compressive Sampling
Compressive Sampling fractional Brownian motion interpolation financial time-series fractal
2011/6/21
This paper proposes a new fBm (fractional Brownian
motion) interpolation/reconstruction method from partially
known samples based on CS (Compressive Sampling). Since 1/f
property implies power law ...
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...
Optimum allocation in multivariate stratified random sampling: Stochastic matrix optimisation
Multivariate stratified random sampling modified E-model stochastic programming optimum allocation integer programming E-model V -model P-model
2011/6/17
The allocation problem for multivariate stratified random sampling as a problem of
stochastic matrix integer mathematical programming is considered. With these aims
the asymptotic normality of sampl...
Optimal Multistage Sampling in a Boundary-Crossing Problem
Asymptotic Brownian motion Group sequential Multistage Optimality
2011/6/17
Brownian motion with known positive drift is sampled in stages until
it crosses a positive boundary a. A family of multistage samplers that con-
trol the expected overshoot over the boundary by vary...
Approximate inference via variational sampling
variational sampling limit theorem probability distribution
2011/6/16
We propose a new method to approximately integrate a function with respect
to a given probability distribution when an exact computation is intractable. The
method is called \variational sampling" a...
Metamodel-based importance sampling for structural reliability analysis
reliability analysis importance sampling metamodeling error kriging random fields active learning rare events
2011/6/16
Structural reliability methods aim at computing the probability of failure of systems with
respect to some prescribed performance functions. In modern engineering such functions
usually resort to ru...