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Academy of Mathematics and Systems Science, CAS Colloquia & Seminars：Subsampling for Rare Events Data and maximum sampled conditional likelihood
罕见事件数据 子采样 最大采样 条件似然
2023/5/15
In this talk, we show that the available information about unknown parameters in rare events data is only tied to the relatively small number of cases, which justifies the usage of negative sampling. ...
High Dimensional Generalized Empirical Likelihood for Moment Restrictions with Dependent Data
Generalized empirical likelihood High dimensionality Penalized likelihood Variable selec- tion
2016/1/26
This paper considers the maximum generalized empirical likelihood (GEL) estimation and inference on parameters identified by high dimensional moment restrictions with weakly dependent data when the di...
Marginal empirical likelihood and sure independence screening
Empirical likelihood high dimensional data analysis independence sure screening large deviation
2016/1/25
We study a marginal empirical likelihood approach in scenarios when the num-ber of variables grows exponentially with the sample size. The marginal empirical likelihood ratios as functions of the para...
Maximum-Likelihood Estimation For Diffusion Processes Via Closed-Form Density Expansions
asymptotic expansion diffusion discrete observation maximum-likelihood estimation transition density
2016/1/25
This paper proposes a widely applicable method of approximate maximum-likelihood estimation for multivariate diffusion process from discretely sampled data. A closed-form asymptotic expansion for tran...
Jackknife Empirical Likelihood Method for Some Risk Measures and Related Quantities
Confidence interval jackknife empirical likelihood risk measure
2016/1/25
Quantifying risks is of importance in insurance. In this paper, we employ the jackknife empirical likelihood method to construct confidence intervals for some risk measures and related quantities stud...
High Dimensional Generalized Empirical Likelihood for Moment Restrictions with Dependent Data
Generalized empirical likelihood High dimensionality Penalized likelihood
2016/1/20
This paper considers the maximum generalized empirical likelihood (GEL) estimation and inference on parameters identified by high dimensional moment restrictions with weakly dependent data when the di...
Marginal empirical likelihood and sure independence screening
Empirical likelihood high dimensional data analysis independence sure screening large deviation
2016/1/20
We study a marginal empirical likelihood approach in scenarios when the num-ber of variables grows exponentially with the sample size. The marginal empirical likelihood ratios as functions of the para...
Maximum-Likelihood Estimation For Diffusion Processes Via Closed-Form Density Expansions
asymptotic expansion diffusion discrete observation maximum-likelihood estimation transition density
2016/1/20
This paper proposes a widely applicable method of approximate maximum-likelihood estimation for multivariate diffusion process from discretely sampled data. A closed-form asymptotic expansion for tran...
On the Approximate Maximum Likelihood Estimation for Diffusion Processes
Asymptotic expansion Asymptotic normality Consistency Dis- crete time observation Maximum likelihood estimation
2016/1/19
The transition density of a diffusion process does not admit an explicit expression in general, which prevents the full maximum likelihood estimation (MLE) based on discretely observed sample paths. A...
Jackknife Empirical Likelihood for Parametric Copulas
Copulas Empirical likelihood Interval estimation Jackknife
2016/1/19
For fitting a parametric copula to multivariate data, a popular way is to employ the so-called pseudo maximum likelihood estimation proposed by Genest, Ghoudi and Rivest (1995). Although interval esti...
Likelihood Bounds for Constrained Estimation with Uncertainty
Likelihood Bounds Constrained Estimation Uncertainty
2015/7/10
This paper addresses the problem of finding bounds on the optimal maximum a posteriori (or maximum likelihood) estimate in a linear model under the presence of model uncertainty. We introduce the nove...
Likelihood Geometry
Likelihood Geometry
2013/6/17
We study the critical points of monomial functions over an algebraic subset of the probability simplex. The number of critical points on the Zariski closure is a topological invariant of that embedded...
Comparing composite likelihood methods based on pairs for spatial Gaussian random fieldsM
Covariance estimation Geostatistics Large datasets Tapering
2013/6/14
In the last years there has been a growing interest in proposing methods for estimating covariance functions for geostatistical data. Among these, maximum likelihood estimators have nice features when...
Likelihood-free Simulation-based Optimal Design
Simulation based optimal design approximate Bayesian computation Markov chain Monte Carlo
2013/6/14
Simulation-based optimal design techniques are a convenient tool for solving a particular class of optimal design problems. The goal is to find the optimal configuration of factor settings with respec...
MCMC methods for Gaussian process models using fast approximations for the likelihood
MCMC methods for Gaussian process models using fast approximations for the likelihood
2013/6/14
Gaussian Process (GP) models are a powerful and flexible tool for non-parametric regression and classification. Computation for GP models is intensive, since computing the posterior density, $\pi$, fo...