Inner Statistical Inference II

Procrustean statistical inference of deformations

A two step method has been devised for the statistical inference of deformation changes. In the first step of this method and based on Procrustes analysis of deformation tensors, the significance of the change in a time or space series of deformation tensors is statistically analyzed. In the second step significant change(s) in deformations are localized. In other words, they are assigned to ce...

Statistical Inference for the Lomax Distribution under Progressively Type-II Censoring with Binomial Removal

This paper considers parameter estimations in Lomax distribution under progressive type-II censoring with random removals, assuming that the number of units removed at each failure time has a binomial distribution. The maximum likelihood estimators (MLEs) are derived using the expectation-maximization (EM) algorithm. The Bayes estimates of the parameters are obtained using both the squared erro...

Statistical Inference

At the heart of statistics lie the ideas of statistical inference. Methods of statistical inference enable the investigator to argue from the particular observations in a sample to the general case. In contrast to logical deductions made from the general case to the specific case, a statistical inference can sometimes be incorrect. Nevertheless, one of the great intellectual advances of the twe...

Statistical Inference

λn = f1(x1)f1(x2) · · · f1(xn) f0(x1)f0(x2) · · · f0(xn) where we have simplified the notation by writing f0(x) for f(x | θ0) and f1(x) for f(x | θ1). A Likelihoodist Statistician would find the likelihood ratio λn to be the best direct measure of the relative support of the data for these two hypotheses; a Bayesian statistician with prior probabilities π0 = P[H0] and π1 = P[H1] = (1−π0) would ...

Statistical Inference