In these four lectures I cover a number of topics in cosmological data analysis. I concentrate on general techniques which are common in cosmology, or techniques which have been developed in a cosmological context. In fact they have very general applicability, for problems which are firmly model-based, and thus lend themselves to a Bayesian treatment. We consider the general problem of estimati...

one of the interesting topics on multimedia domain is concerned with empowering computer in order to speech production. speech synthesis is granting human abilities to the computer for speech production. data-based approach and process-based approach are the two main approaches on speech synthesis. each approach has its varied challenges. unit-selection speech synthesis and statistical parametr...

Study objective: The purpose of this paper is to give an overview and comparison of different easily applicable statistical techniques to analyse recurrent event data. Setting: These techniques include naive techniques and longitudinal techniques such as Cox regression for recurrent events, generalised estimating equations (GEE), and random coefficient analysis. The different techniques are ill...

STUDY OBJECTIVE The purpose of this paper is to give an overview and comparison of different easily applicable statistical techniques to analyse recurrent event data. SETTING These techniques include naive techniques and longitudinal techniques such as Cox regression for recurrent events, generalised estimating equations (GEE), and random coefficient analysis. The different techniques are ill...

We consider a discriminative learning (regression) problem, whereby the regression function is a convex combination of k linear classifiers. Existing approaches are based on the EM algorithm, or similar techniques, without provable guarantees. We develop a simple method based on spectral techniques and a ‘mirroring’ trick, that discovers the subspace spanned by the classifiers’ parameter vector...

Forecasting rice production is a challenging problem in agricultural statistics. The inherent difficulty lies in demand and supply affected by many uncertain factors viz. economic policies, agricultural factors, credit measures, foreign trade etc. which interact in a complex manner. Since last few decades, Statistical techniques are used for developing predictive models to estimate required par...