We undertake an experimental study about road-hauliers’ choice between railways and roads. If road hauliers choose to load their truck on a train, they are not able to switch to using the road again until they reach the end of the line. On the contrary, highway choice is flexible in that the road haulier can change road at any time. Building upon the irreversibility of one of the two choices, w...

We study the non-parametric isotonic regression problem for bivariate elicitable functionals that are given as an univariate functional and its Bayes risk. Prominent examples of this type (mean, variance) (Value-at-Risk, Expected Shortfall), where latter pair consists important risk measures in finance. present our results totally ordered covariates but extenstions to partial orders appendix.

The problem considered is sequential estimation of the mean 0 of a one-parameter exponential family of distributions with squared error loss for estimation error and a cost c > 0 for each of an i.i.d, sequence of potential observations X 1, X 2 . . . . . A Bayesian approach is adopted, and natural conjugate prior distributions are assumed. For this problem, the asymptotically pointwise optimal ...

We present a Minimum Bayes Risk (MBR) decoder for statistical machine translation. The approach aims to minimize the expected loss of translation errors with regard to the BLEU score. We show that MBR decoding on N -best lists leads to an improvement of translation quality. We report the performance of the MBR decoder on four different tasks: the TCSTAR EPPS Spanish-English task 2006, the NIST ...

Collaborative Spectrum Sensing (CSS) is an effective approach to improve the detection performance in Cognitive Radio (CR) networks. Inherent characteristics of the CR have imposed some additional security threats to the networks. One of the common threats is Primary User Emulation Attack (PUEA). In PUEA, some malicious users try to imitate primary signal characteristics and defraud the CR user...

Minimum Bayes Risk (MBR) decoders improve upon MAP decoders by directly optimizing loss function of interest: Word Error Rate MBR decoding is expensive when the search spaces are large Segmental MBR (SMBR) decoding breaks the single utterance-level MBR decoder into a sequence of simpler search problems. – To do this, the N-best lists or lattices need to be segmented We present: A new lattice se...

Consider an experiment yielding an observable random quantity X whose distribution Fθ depends on a parameter θ with θ being distributed according to some distribution G0. We study the Bayesian estimation problem of θ under squared error loss function based on X, as well as some additional data available from other similar experiments according to an empirical Bayes structure. In a recent paper,...

In this paper, decision theory was used to derive Bayes and minimax decision rules to estimate allelic frequencies and to explore their admissibility. Decision rules with uniformly smallest risk usually do not exist and one approach to solve this problem is to use the Bayes principle and the minimax principle to find decision rules satisfying some general optimality criterion based on their ris...

The growth of credit card application needs to be balanced with the anticipation of bad credit risk because it does not use security collateral as warranty. The usage of credit scoring can be used to help the credit risk analysis in determining the applicant's eligibility. Data mining has been proven as a valuable tool for credit scoring. The aim of this research is to design a data mining mode...

This paper deals with Bayesian models given by statistical experiments and standard loss functions. Bayes probability of error and Bayes risk are estimated by means of classical and generalized information criteria applicable to the experiment. The accuracy of the estimation is studied. Among the information criteria studied in the paper is the class of posterior power entropies which includes ...