Khwazbeen Saida Fatah

Salahaddin University - Erbil | SUH · Department of Mathematics

The Interval Dependence Structure (IDS) and Local Dependence Function (LDF) are tools used to measure possible changes that occur in the correlation of bivariate random variables at each point acrossthe whole domain. Bivariate distribution functionswith Gamma marginals are used to construct correlated models that joint a widespread variety of data...

The Non-homogeneous Poisson Process, with time dependent intensity functions, is commonly used to model the scenarios of counting the number of events that appear to take place in a given time interval. The identification of the process relies on the functional form for the intensity function, which can be difficult to determine. In this paper, a N...

In multivariate survival analysis, estimating the multivariate distribution functions and then measuring the association between survival times are of great interest. Copula functions, such as Archimedean Copulas, are commonly used to estimate the unknown bivariate distributions based on known marginal functions. In this paper the feasibility of us...

This paper discusses the problem of parametric analysis of a probability distribution known as type I and II Marshall-Olkin bivariate Weibull distribution, which is frequently used in the analysis of survival and reliability. It is remarkable that there is no specific technique for fitting the bivariate right-censored failure time data to type II...

Logistic Regression Analysis describes how a response variable having two or more categories is associated with a set of predictor variables (continuous or categorical) through a probability function. When the response variable is with only two categories a Binary Logistic Regression Model is the most widely used approach. The main deficiency with...

In ranking decision alternatives, Analytic Hierarchy Process is regarded as one of the most successful techniques to deal with multiple criteria decision making problems. Recognizing that tender evaluation is a typical multi-criteria decision making problem, this paper introduces an evaluation approach based on AHP methodology for ranking various a...

Regression models are considered as the most commonly used statistical analysis techniques to describe the functional relationships between a dependent variable (either continuous or categorical) and a set of independent variables based on samples from a particular population. In this paper, a Multinomial Logistic Regression Model is proposed to in...

In this paper, we propose a new risk-preference model for ranking pairs of normalised lotteries, random variables, each represents a risk factor obtained by converting the outcomes of the lottery into its mean multiplied by a risk factor. With the existence of an expected utility model, the preference ordering over a pair of such lotteries is conve...

In decision-making problems under uncertainty, mean-variance analysis consistent with expected utility theory plays an important role in analysing preferences for different alternatives. In this paper, a new approach for mean-variance analysis based on cumulative distribution functions is proposed. Using simulation, a new algorithm is developed, wh...