This paper considers inference under progressive type II censoring with a compound Rayleigh failure time distribution. The maximum likelihood (ML), and Bayes methods are used for estimating the unknown parameters as well as some lifetime parameters, namely reliability and hazard functions. We obtained Bayes estimators using the conjugate priors for two shape and scale parameters. When the two p...

Importance sampling is a classical Monte Carlo technique in which a random sample from one probability density, π1, is used to estimate an expectation with respect to another, π. The importance sampling estimator is strongly consistent and, as long as two simple moment conditions are satisfied, it obeys a central limit theorem (CLT). Moreover, there is a simple consistent estimator for the asym...

Attribute-based encryption (ABE) is an exciting alternative to public-key encryption, as ABE develops encryption systems with high expressiveness, without the need for a public key infrastructure (PKI) that makes publicly available the mapping between identities (sets of attributes), public keys, and validity of the latter. Any setting, PKI or attribute-based, must provide a means to revoke use...

We propose a simple abstract formalisation of the act of observation, in which the system and the observer are assumed to be in a pure state and their interaction deterministically changes the states such that the outcome can be read from the state of the observer after the interaction. If the observer consistently realizes the outcome which maximizes the likelihood ratio that the outcome perta...

Lexical-Functional Grammar (Kaplan and Bresnan, 1982) f-structures are bilexical labelled dependency representations. We show that the Naive Bayes classifier is able to guess missing grammatical function labels (i.e. bilexical dependency labels) with reasonably high accuracy (82–91%). In the experiments we use f-structure parser output for English and German Europarl data, automatically “broken...

This paper provides the Bayes estimators of the failure rate and reliability function for a one-parameter, exponential distribution by utilizing a point guess estimate of the parameter. For deriving the Bayes estimators, the prior distributions are chosen such that they are centered at the known prior values of parameters. The validity of proposed estimators is examined with respect to their ma...

The minimum covariance determinant (MCD) method is a robust estimator of multivariate location and scatter (Rousseeuw, 1984). The MCD is highly resistant to outliers, and it is often applied by itself and as a building block for other robust multivariate methods. Computing the exact MCD is very hard, so in practice one resorts to approximate algorithms. Most often the FASTMCD algorithm of Rouss...