In this work we explore possibilities for coding and decoding tailor-made for mean squared error evaluation of error in contexts such as image transmission. To do so, we introduce a loss function that expresses the overall performance of a coding and decoding scheme for discrete channels and that exchanges the usual goal of minimizing the error probability to that of minimizing the expected los...

porosity is one of the fundamental petrophysical properties that should be evaluated for hydrocarbon bearing reservoirs. it is a vital factor in precise understanding of reservoir quality in a hydrocarbon field. log data are exceedingly crucial information in petroleum industries, for many of hydrocarbon parameters are obtained by virtue of petrophysical data. there are three main petrophysical...

This paper aims to investigate the effect of budget deficit shock on government spending in Indonesia. For this propose, this reasearch uses an alternative error correction model based on loss function of government spending. The model assumes the short run disequilibrium, in which shock variables may play an important role. A spesific loss function model is applied to develop the long run gove...

This paper considers the Bayesian point estimation of the scale parameter for a two-parameter gamma life-testl,g model In presence of several outller observations in the data. The Bayesian analysis is carried out under the assumption of squared error loss function and fixed or random shape parameter.

This paper addresses the issue of cell loss and its consequent effect on video quality in a packet video system, and examines possible compensative measures. In the system's enconder, adaptive spectral separation is used to develop a two-layer coding scheme comprising a high priority layer to carry essential video data and a low priority layer with data to enhance the video image. A two-step er...

In this paper, we discuss the statistical inference on the unknown parameters and reliability function of type-II extreme value (EVII) distribution when the observed data are progressively type-II censored. By applying EM algorithm, we obtain maximum likelihood estimates (MLEs). We also suggest approximate maximum likelihood estimators (AMLEs), which have explicit expressions. We provide Bayes ...

P erhaps the most surprising result in Statistics arises in a remarkably simple estimation problem. Let X1, ..., Xp be independent random variables, with Xi ∼ N(θi , 1) for i = 1, ..., p. Writing X = (X1, ..., Xp), suppose we want to find a good estimator θ̂ = θ̂(X) of θ = (θ1, ..., θp). To define more precisely what is meant by a good estimator, we use the language of statistical decision theory...

We consider an online matrix prediction problem. FTRL is a standard method to deal with online prediction tasks, which makes predictions by minimizing the cumulative loss function and the regularizer function. There are three popular regularizer functions for matrices, Frobenius norm, negative entropy and log-determinant. We propose an FTRL based algorithm with log-determinant as the regularize...

We derive a lower bound on the differential entropy of a log-concave random variable X in terms of the p-th absolute moment of X. The new bound leads to a reverse entropy power inequality with an explicit constant, and to new bounds on the rate-distortion function and the channel capacity. Specifically, we study the rate-distortion function for log-concave sources and distortion measure |x− x̂|,...