\1ode (also called \1AP\ estimation. mean esumation and median estimation are examined here to determine when they can be 'afely used to derive (posterior) cost mmimwng estimates. !These are all Bayes procedures. using the mode. mean. or median of the posterior distnbu· lion.) [t is found that modal estimation only returns cost m1mmizmg estimates when the cost function is 0L. [f the cost funcuo...

Objectives: The present study aimed to provide an estimation of the current financial burden of renal transplantation therapy for insurance organisations.Methods: An Excel-based model was developed to determine the treatment costs of current clinical practice in renal transplantation therapy (RTT). Inputs were derived from Ministry of Health and insurance organizations` database, hospital and p...

Software metrics are currently used in the industry mainly for cost and effort estimation, while some research suggested their use as fault indicators. There are very few empirical studies in software measurement, especially in the realm of object-oriented metrics. There is no record of management system assessment using software metrics. In this paper we discuss the use of the established obje...

Existing algorithmic models fail to produce accurate software development effort estimates. To address this problem, a case-based reasoning model, called Estor, was developed based on the verbal protocols of a human expert solving a set of estimation problems. Estor was then presented with 15 software effort estimation tasks. The estimates of Estor were compared to those of the expert as well a...

This paper deals with the problem of software effort estimation through the use of a new machine learning technique for producing reliable confidence measures in predictions. More specifically, we propose the use of Conformal Predictors (CPs), a novel type of prediction algorithms, as a means for providing effort estimations for software projects in the form of predictive intervals according to...