Data Envelopment Analysis (DEA) is a technique used to compare efficiency in various sectors such as hospitals, chain stores, and dealerships. It represents a set of linear programming techniques and uses deter-ministic data (inputs and outputs), in stable conditions. The DEA technique cannot be used when there is data with indeterministic nature, or when there is an environment with dynamic co...

one of the water resources modeling requirements is sufficient knowledge of long-term series of meteorological and hydrological parameters. in this study the nearest neighbor resampling method presented by lall and sharma was developed. in the developed model, the knn regression was used for time series forecasting instead of local polynomial used in the developed algorithm by prairie. in this ...

Recently, there has been much interest in accurate determination of mobile user locations in cellular environments. A general approach to this geolocation problem is to gather time-of-arrival measurements from a number of base stations (BSs) and to estimate user locations using the traditional least square approach. However, in non-line-of-sight (NLOS) situations, measurements are significantly...

The non-parametric Bayes estimator with Dirichlet process prior of a survival function based on right censored data was considered by Susarla and Van Ryzin (1976) and many others. We obtain the non-parametric Bayes estimator of a survival function when data are right, left or interval censored. The resulting Bayes estimator with Dirichlet process prior has an explicit formula. In contrast, ther...

Similarity scores represent the basis for identity inference in biometric verification systems. However, because of the so-called miss-matched conditions across enrollment and probe samples and identity-dependent factors these scores typically exhibit statistical variations that affect the verification performance of biometric systems. To mitigate these variations, scorenormalisation techniques...

A trenchant and passionate dispute over the use of parametric versus non-parametric methods for the analysis of Likert scale ordinal data has raged for the past eight decades. The answer is not a simple "yes" or "no" but is related to hypotheses, objectives, risks, and paradigms. In this paper, we took a pragmatic approach. We applied both types of methods to the analysis of actual Likert data ...