Approximate Bayesian Computation for a Class of Time Series Models

In the following article we consider approximate Bayesian computation (ABC) for certain classes of time series models. In particular, we focus upon scenarios where the likelihoods of the observations and parameter are intractable, by which we mean that one cannot evaluate the likelihood even up-to a positive unbiased estimate. This paper reviews and develops a class of approximation procedures based upon the idea of ABC, but, specifically maintains the probabilistic structure of the original statistical model. This idea is useful, in that it can facilitate an analysis of the bias of the approximation and the adaptation of established computational methods for parameter inference. Several existing results in the literature are surveyed and novel developments with regards to computation are given

Measurement of Electroweak Vector Boson Pair Production in pp Collision with the CMS Detector at LHC

We present an overview of measurements of electroweak vector boson pair production and anomalous Triple Gauge Couplings (aTGC), with semileptonic and fully leptonic final states. The data analyzed were taken at center of mass energy of 7 & 8 TeV by the CMS detector at the Large Hadron Collider. The cross-section measurements are important because they are test of the Standard Model predictions, while these processes serve as background for Higgs searches and various other processes