http://hdl.handle.net/10016/9041 2013-05-20T12:31:01Z 2013-05-20T12:31:01Z Luengo García, David Martino, Luca http://hdl.handle.net/10016/16645 2013-04-17T08:04:07Z 2012-02-29T23:00:00Z

Title: Efficient random variable generation: ratio of uniforms and polar rejection sampling Author(s): Luengo García, David; Martino, Luca Abstract: Monte Carlo techniques, which require the generation of samples from some target density, are often the only alternative for performing Bayesian inference. Two classic sampling techniques to draw independent samples are the ratio of uniforms (RoU) and rejection sampling (RS). An efficient sampling algorithm is proposed combining the RoU and polar RS (i.e. RS inside a sector of a circle using polar coordinates). Its efficiency is shown in drawing samples from truncated Cauchy and Gaussian random variables, which have many important applications in signal processing and communications.

2012-02-29T23:00:00Z Martino, Luca Luengo García, David Míguez Arenas, Joaquín http://hdl.handle.net/10016/16644 2013-04-25T07:44:13Z 2012-10-31T23:00:00Z

Title: Efficient sampling from truncated bivariate Gaussians via Box-Muller transformation Author(s): Martino, Luca; Luengo García, David; Míguez Arenas, Joaquín Abstract: Many practical simulation tasks demand procedures to draw samples efficiently from multivariate truncated Gaussian distributions. Introduced is a novel rejection approach, based on the Box-Muller transformation, to generate samples from a truncated bivariate Gaussian density with an arbitrary support. Furthermore, for an important class of support regions the new method allows exact sampling to be achieved, thus becoming the most efficient approach possible.Many practical simulation tasks demand procedures to draw samples efficiently from multivariate truncated Gaussian distributions. Introduced is a novel rejection approach, based on the Box-Muller transformation, to generate samples from a truncated bivariate Gaussian density with an arbitrary support. Furthermore, for an important class of support regions the new method allows exact sampling to be achieved, thus becoming the most efficient approach possible.

2012-10-31T23:00:00Z Luengo Garcia, David Martino, Luca http://hdl.handle.net/10016/16643 2013-04-25T07:42:05Z 2012-10-31T23:00:00Z

Title: Almost rejectionless sampling from Nakagami-m distributions (m≥1) Author(s): Luengo Garcia, David; Martino, Luca Abstract: The Nakagami-m distribution is widely used for the simulation of fading channels in wireless communications. A novel, simple and extremely efficient acceptance-rejection algorithm is introduced for the generation of independent Nakagami-m random variables. The proposed method uses another Nakagami density with a half-integer value of the fading parameter, mp=n/2=m, as proposal function, from which samples can be drawn exactly and easily. This novel rejection technique is able to work with arbitrary values of m=1, average path energy, =, and provides a higher acceptance rate than all currently available methods.

2012-10-31T23:00:00Z Martino, Luca Pascual Del Olmo, Víctor Read, Jesse Michael http://hdl.handle.net/10016/16641 2013-04-17T07:48:49Z 2012-06-30T22:00:00Z

Title: A multi-point Metropolis scheme with generic weight functions Author(s): Martino, Luca; Pascual Del Olmo, Víctor; Read, Jesse Michael Abstract: The multi-point Metropolis algorithm is an advanced MCMC technique based on drawing several correlated samples at each step and choosing one of them according to some normalized weights. We propose a variation of this technique where the weight functions are not specified, i.e., the analytic form can be chosen arbitrarily. This has the advantage of greater flexibility in the design of high-performance MCMC samplers. We prove that our method fulfills the balance condition, and provide a numerical simulation. We also give new insight into the functionality of different MCMC algorithms, and the connections between them.

2012-06-30T22:00:00Z