Search Results - subject:"Sequential importance sampling"

A sequential importance sampling for estimating multi-period tail risk

Seo, Ye-Ji; Kim, Sunggon - In: Risks : open access journal 12 (2024) 12, pp. 1-22

. To overcome this shortcoming, we propose a sequential importance sampling, which is a modification of CMC. In the … VaRs and ESs by the proposed method, and to compare the performance of the proposed sequential importance sampling with CMC. …

Persistent link: https://www.econbiz.de/10015328727

Tail Distribution of the Maximum of Correlated Gaussian Random Variables

Botev, Zdravko; Mandjes, Michel; Ridder, Ad - 2015

completely new sequential importance sampling estimator of the desired tail probability. Numerical experiments suggest that the … sequential importance sampling estimator can be significantly more efficient than its competitor. …

Persistent link: https://www.econbiz.de/10011451510

Tail distribution of the maximum of correlated Gaussian random variables

Botev, Zdravko I.; Mandjes, Michel; Ridder, Ad - 2015

Persistent link: https://www.econbiz.de/10011431354

The Gibbs sampler with particle efficient importance sampling for state-space models

Grothe, Oliver; Kleppe, Tore Selland; Liesenfeld, Roman - In: Econometric reviews 38 (2019) 10, pp. 1152-1175

Persistent link: https://www.econbiz.de/10012181399

Sequential Monte Carlo for Counting Vertex Covers in General Graphs

Vaisman, Radislav; Botev, Zdravko; Ridder, Ad - 2013

In this paper we describe a Sequential Importance Sampling (SIS) procedure for counting the number of vertex covers in …

Persistent link: https://www.econbiz.de/10010326237

Sequential Monte Carlo for Counting Vertex Covers in General Graphs

Vaisman, Radislav; Botev, Zdravko; Ridder, Ad - Tinbergen Instituut - 2013

In this paper we describe a Sequential Importance Sampling (SIS) procedure for counting the number of vertex covers in …

Persistent link: https://www.econbiz.de/10011257010

Sequential Monte Carlo for counting vertex covers in general graphs

Vaisman, Radislav; Botev, Zdravki I.; Ridder, Ad - 2013

Persistent link: https://www.econbiz.de/10010191297

Dynamic Entry with Cross Product Spillovers: An Application to the Generic Drug Industry

Hong, Han; Khwaja, Ahmed; Gallant, A. Ronald - Duke University, Department of Economics - 2010

challenge of estimating such a model using a sequential importance sampling based technique. Our estimates show significant …

Persistent link: https://www.econbiz.de/10008764960

Parameter estimation via stochastic variants of the ECM algorithm with applications to plant growth modeling

Trevezas, S.; Malefaki, S.; Cournède, P.-H. - In: Computational Statistics & Data Analysis 78 (2014) C, pp. 82-99

maximization (ECM) algorithm was adopted, where the E-step was approximated by sequential importance sampling with resampling (SISR …

Persistent link: https://www.econbiz.de/10010871385

Permanents, <InlineEquation ID="IEq1"> <EquationSource Format="TEX">$$\alpha $$</EquationSource> <EquationSource Format="MATHML"> <math xmlns:xlink="http://www.w3.org/1999/xlink"> <mi mathvariant="italic">α</mi> </math> </EquationSource> </InlineEquation>-permanents and Sinkhorn balancing

Sullivan, Francis; Beichl, Isabel - In: Computational Statistics 29 (2014) 6, pp. 1793-1798

The method of Sinkhorn balancing that starts with a non-negative square matrix and iterates to produce a related doubly stochastic matrix has been used with some success to estimate the values of the permanent in some cases of physical interest. However, it is often claimed that Sinkhorn...

Persistent link: https://www.econbiz.de/10011151865