Genomic selection is a genetic evaluation of animals from their DNA (extracted using biological samples such as blood or hairs, or biopsy), based on a huge number of markers covering the whole genome. The basic principle was established by Meuwissen, Hayes and Goddard in 2001 [4]. In this context, an important objective of genomic selection consists in searching explicative markers for a phenot...

A 7-step method (with 25 sub-steps) to assess risk of air pollutants is introduced. These steps are: pre-considerations, sampling, statistical analysis, exposure matrix and likelihood, doseresponse matrix and likelihood, total risk evaluation, and discussion of findings. All mentioned words and expressions are wellunderstood; however, almost all steps have been modified, improved, and coupled i...

Statistical model selection criteria provide an informed choice of the model with best external (i.e., out-of-sample) validity. Therefore they guard against overfitting (“data snooping”). We implement several model selection criteria in order to verify recent evidence of predictability in excess stock returns and to determine which variables are valuable predictors. We confirm the presence of i...

Bioequivalence and clinical equivalence trials evaluate the similarity of two or more treatments. For continuous responses, equivalence is demonstrated if a 90% confidence interval for the ratio of treatment means is contained within a prespecified limit, usually 0.8-1.25. When multiple response criteria are evaluated, investigators might conclude overall treatment equivalence if equivalence is...

PURPOSE Identification of potential shared primary psychoprophylaxis and crime prevention is measured by analyzing the rate of commitments for patients-subjects to forensic examination. MATERIAL AND METHOD The statistic trial is a retrospective, document-based study. The statistical lot consists of 770 initial examination reports performed and completed during the whole year 2007, primarily a...

We present two new algorithms for multimodal, dense matching of two images using a variational approach. These algorithms complete and generalise our previous work by treating the case of semi-local energy functionals. In brief, they are derived from the maximization of two statistical criteria (mutual information and correlation ratio) estimated from corresponding regions around each pixel (or...

Since the 1990s, the Akaike Information Criterion (AIC) and its various modifications/extensions, including BIC, have found wide applicability in econometrics as objective procedures that can be used to select parsimonious statistical models. The aim of this paper is to argue that these model selection procedures invariably give rise to unreliable inferences, primarily because their choice with...

BACKGROUND Sometimes, protocol amendments that change the inclusion and exclusion criteria are required in clinical trials. Then, the patient populations before and after the amendment may differ. METHODS We propose to perform separate statistical tests for the different phases, i.e. for the patients recruited before and after the amendment, and to combine the tests using Fisher's combination...

We study two related topics in decision fusion for multisensor image classification. The first topic is the use of a weighted logarithmic opinion pool compared to the statistical product combination rule. The performance is compared on three data sets. The second topic is related to different criteria for parameter estimation for a statistical fusion model. We propose an alternative criterion f...

Since the 1990’s the Akaike Information Criterion (AIC) and its various modifications/extensions have found wide applicability in econometrics as objective procedures which can be used to select parsimonious statistical models. The aim of this paper is to argue that these model selection procedures invariably give rise to unreliable inferences primarily because their choice within a prespecifie...