Search Results - subject:"Importance resampling"

Learning and filtering via simulation: smoothly jittered particle filters

Shephard, Neil; Flury, Thomas - Department of Economics, Oxford University - 2009

A key ingredient of many particle filters is the use of the sampling importance resampling algorithm (SIR), which …

Persistent link: https://www.econbiz.de/10008497742

On the convergence of quasi-random sampling/importance resampling

Vandewoestyne, Bart; Cools, Ronald - In: Mathematics and Computers in Simulation (MATCOM) 81 (2010) 3, pp. 490-505

multiplicative constant. The sampling/importance resampling (SIR) algorithm is known to be useful in this context. Moreover, the … quasi-random sampling/importance resampling (QSIR) scheme, based on quasi-Monte Carlo methods, is a more recent modification …

Persistent link: https://www.econbiz.de/10010870235

Two noniterative algorithms for computing posteriors

Yang, Jun; Zou, Guohua; Zhao, Yu - In: Computational Statistics 23 (2008) 3, pp. 443-453

Persistent link: https://www.econbiz.de/10005613217

Posterior analysis of lognormal regression models using the Gibbs sampler

Upadhyay, S.; Peshwani, M. - In: Statistical Papers 49 (2008) 1, pp. 59-85

Persistent link: https://www.econbiz.de/10008533804

Pooling and Dynamic Forgetting Effects in Multitheme Advertising: Tracking the Advertising Sales Relationship with Particle Filters

Bruce, Norris I. - In: Marketing Science 27 (2008) 4, pp. 659-673

Firms often use a pool or series of advertising themes in their campaigns. Thus, for example, a firm may employ some of its advertising to promote price-related themes or messages and other of its advertising to promote product-related themes. This study examines the interdependence that can...

Persistent link: https://www.econbiz.de/10008787687