On weighting of bivariate margins in pairwise likelihood

Master Thesis PREDICTION BASED ON PAIRWISE LIKELIHOOD

A re-weighting strategy for improving margins

We present a simple general scheme for improving margins that is inspired on well known margin theory principles. The scheme is based on a sample re-weighting strategy. The very basic idea is in fact to add to the training set new replicas of samples which are not classified with a sufficient margin. As a study case, we present a new algorithm, namely TVQ, which is an instance of the proposed s...

Cutset Sampling with Likelihood Weighting

The paper extends the principle of cutset sampling over Bayesian networks, presented previously for Gibbs sampling, to likelihood weighting (LW). Cutset sampling is motivated by the Rao-Blackwell theorem which implies that sampling over a subset of variables requires fewer samples for convergence due to the reduction in sampling variance. The scheme exploits the network structure in selecting c...

the impact of e-readiness on ec success in public sector in iran the impact of e-readiness on ec success in public sector in iran

acknowledge the importance of e-commerce to their countries and to survival of their businesses and in creating and encouraging an atmosphere for the wide adoption and success of e-commerce in the long term. the investment for implementing e-commerce in the public sector is one of the areas which is focused in government‘s action plan for cross-disciplinary it development and e-readiness in go...

Comments on Pairwise Likelihood in Time Series Models

This note is concerned with the asymptotic properties of pairwise likelihood estimation procedures for linear time series models. The latter includes ARMA as well as fractionally integrated ARMA processes, where the fractional integration parameter d < 0.5. In some cases, including AR(1) processes and longmemory processes with d < 0.25, the loss in efficiency in using pairwise likelihood method...