In this note we introduce some divergence-based model selection criteria. These criteria are defined by estimators of the expected overall discrepancy between the true unknown model and the candidate model, using dual representations of divergences and associated minimum divergence estimators. It is shown that the proposed criteria are asymptotically unbiased. The influence functions of these c...

This research set out to find out the mate selection criteria among single female teachers. This qualitative study was carried out via thematic analysis approach. Using purposive sampling method, 15 single female teachers aged 18 to 30 years old were identified in Tehran and fifteen semi-structured interviews were conducted. The interviews were recorded, transcribed and then were analyzed using...

CONTEXT Acute tibial shaft fractures represent one of the most severe injuries in sports. Return rates and return-to-sport times after these injuries are limited, particularly with regard to the outcomes of different treatment methods. OBJECTIVE To determine the current evidence for the treatment of and return to sport after tibial shaft fractures. DATA SOURCES OVID/MEDLINE (PubMed), EMBASE...

OBJECTIVE To determine if there is evidence that equipment use reduces sport concussion risk and/or severity. DATA SOURCES 12 electronic databases were searched using a combination of Medical Subject Headings and text words to identify relevant articles. REVIEW METHODS Specific inclusion and exclusion criteria were used to select studies for review. Data extracted included design, study pop...

stock selection criteria play a key role in contrarian portfolio construction. the usual approach is applying cumulative return as stock selection criteria however applying this criterion leads to ranking stocks without considering investment risk. in this study, we analyze contrarian strategies that are based on reward–risk stock selection criteria in contrast to ordinary contrarian strategies...

designing an effective criterion for selecting the best rule is a major problem in theprocess of implementing fuzzy learning classifier (flc) systems. conventionally confidenceand support or combined measures of these are used as criteria for fuzzy rule evaluation. in thispaper new entities namely precision and recall from the field of information retrieval (ir)systems is adapted as alternative...

We present a study on a rough set based approach for feature selection. Instead of using significance or support, Parameterized Average Support Heuristic (PASH) considers the overall quality of the potential set of rules. It will produce a set of rules with balanced support distribution over all decision classes. Adjustable parameters of PASH can help users with different levels of approximatio...

Recursive Feature Elimination (RFE) combined with feature ranking is an effective technique for eliminating irrelevant features when the feature dimension is large, but it is difficult to distinguish between relevant and redundant features. The usual method of determining when to stop eliminating features is based on either a validation set or cross-validation techniques. In this paper, we pres...

This is a survey of the information criterion approach to model selection problems. New results about context tree estimation and the estimation of the basic neighborhood of Markov random fields are also mentioned. 1. The model selection problem Let a stochastic process {Xt, t ∈ T } be given, where each Xt is a random variable with values a ∈ A, and T is an index set. The joint distribution of ...

Designing an effective criterion for selecting the best rule is a major problem in theprocess of implementing Fuzzy Learning Classifier (FLC) systems. Conventionally confidenceand support or combined measures of these are used as criteria for fuzzy rule evaluation. In thispaper new entities namely precision and recall from the field of Information Retrieval (IR)systems is adapted as alternative...