Fatimah Almulhim

• Doctor of Philosophy
• Professor (Assistant) at Princess Nourah bint Abdulrahman University

This paper introduces an enhanced class of ratio estimators, which employ the transformation technique on an auxiliary variable under simple random sampling to estimate the population median. The transformation strategy can reduce both the bias and mean square error, which can help estimators become more efficient. The bias and mean square error of...

Two-phase sampling is an effective sampling approach that is useful in sample surveys when prior auxiliary information is not available. When two variables have an association, the ranks of the auxiliary variable are proportional to the study variable. Therefore, we can use these rankings to improve the accuracy of the estimators. In this article,...

This study investigates the computation of fractional and higher integer-order moments for a stochastic process governed by a one-dimensional, non-homogeneous linear stochastic differential equation (SDE) driven by fractional Brownian motion (fBm). Unlike conventional approaches relying on moment-generating functions or Fokker–Planck equations, whi...

An efficient estimator can reduce both bias and mean squared error to provide more accurate results by using the transformation strategy. In this paper, an enhanced class of ratio–product types of estimators is introduced, which employs the transformation technique by linearly combining two robust measures, the trimean and decile mean, and five non...

This study proposes a continuous probability distribution called the hybrid Weibull inverse Rayleigh distribution (HWIR) with three parameters. This distribution is then expanded to deal with neutrosophic data, whereneutrosophic random variables and parameters are considered based on the direct neutrosophic method. Ourmethodology consists of integr...

A new predictor in functional time series (FTS ) is considered. It is based on the asymmetric weighting function of quantile regression. More precisely, we assume that FTS is generated from a single-index model that permits the observation of endogenous–exogenous variables by combining the nonparametric model with a linear one. In parallel, the L1-...

Ordered set sampling techniques are among the most popular current techniques used in estimation, especially for small sample sizes, and their efficiency has been proven in many articles as the best estimators for unknown parameters for several distributions. Systematic ranked set sampling and centralized ranked set sampling are two recently develo...

We propose a robust procedure to estimate the conditional mode of a univariate outcome O given a Hilbertian explanatory variable I, under the assumption that (O,I) follow a single-index structure. The estimator is constructed using the M-estimator for the conditional density, and we establish its complete convergence. We discuss the estimator’s adv...

This paper considers the Recursive Kernel Estimator (RKE) of the expectile-based conditional shortfall. The estimator is constructed under a functional structure based on the ergodicity assumption. More preciously, we assume that the input-variable is valued in a pseudo-metric space, output-variable is scalar and both are sampled from ergodic funct...

This article defines a new distribution using a novel alpha power-transformed method extension. The model obtained has three parameters and is quite effective in modeling skewed, complex, symmetric, and asymmetric datasets. The new approach has one additional parameter for the model. Certain distributional and mathematical properties are investigat...

The main aim of this paper is to consider a new risk metric that permits taking into account the spatial interactions of data. The considered risk metric explores the spatial tail-expectation of the data. Indeed, it is obtained by combining the ideas of expected shortfall regression with an expectile risk model. A spatio-functional Nadaraya–Watson...

This paper treats the problem of risk management through a new conditional expected shortfall function. The new risk metric is defined by the expectile as the shortfall threshold. A nonparametric estimator based on the Nadaraya–Watson approach is constructed. The asymptotic property of the constructed estimator is established using a functional tim...

In the contemporary era of information technology, copious amounts of data are ubiquitous, generated across various sectors on a daily basis. Analyzing every unit of data is impractical due to constraints such as limited resources in terms of time, labor, and cost. In such scenarios, survey sampling becomes a recommended approach for extracting inf...

This paper deals with the problem of financial risk management using a new expected shortfall regression. The latter is based on the expectile model for financial risk-threshold. Unlike the VaR model, the expectile threshold is constructed by an asymmetric least square loss function. We construct an estimator of this new model using the k-nearest n...

This paper analyzes the co-fluctuation between a scalar response random variable and a curve regressor using quantile regression. We focus on the situation wherein the output variable is observed with random missing. For this incomplete functional data situation, we estimate the quantile regression by combining two principal nonparametric methods:...

This paper proposes a new family of estimators for population mean with a non-response using a simple random sampling. It specifically applies this method to estimate the mean in Turkey's Education sector data sets, accounting for non-response. The study integrates additional information in the form of mean and cdf of the auxiliary variable which i...

This paper addresses some classes of combined and separate imputation methods (CSIMs) of the population mean under stratified simple random sampling (SSRS) along with their characteristics. To the best of our knowledge, these imputation methods (IMs) have yet not been studied by any author under SSRS, hence these IMs are called 'novel'. In addition...

The usefulness of a new heavy-tailed distribution is studied in this article. The type-I heavy-tailed exponential (TI-HTE) distribution studied here has been suggested in the literature but has not been studied anywhere other than now. Some of its properties, together with graphical representations, were considered. The study utilized the maximum l...

In this article, we offer simple random sampling (SRS) based efficient class of estimators of population mean utilizing additional information. The expression of the mean square error of the proposed class of estimators is deduced up to first degree approximation. The efficiency conditions are established which are enhanced numerically utilizing a...

When population units fail for several reasons, the competing risks model is triggered. The failure time and associated reason of failure are noted in this model. It is possible to partially observe the reasons why the competing risks model fails. In this work, where the failure time is distributed with the power hazard rate distribution, we utiliz...

Scatterometry is a technique used to transmit radio or microwaves to examine different geophysical properties, wind speed, and direction. Precise and rapid weather predictions become essential in several applications in assisting planning and management in response to weather conditions. At the same time, timely wind speed prediction gains consider...

An intriguing mechanism that facilitates easy connection between several devices is the internet of things (IoT). This encourages the creation of fresh methods for automatically detecting client IoT occurrence traffic. Through this study, we show that several kinds of machine learning methods may produce great accurateness distributed denial of ser...

Russia and Ukraine got into an armed conflict on 24𝑡ℎ February 2022. In addition, the World Health Organisation still warns of a fast growth in infections and deaths. Infectious disease remains a serious issue in Ukraine and poorly governed cities, such as those in armed conflicts. During this period of security instability, the coronavirus situati...

This article presents and investigates a modified version of the Weibull distribution that incorporates four parameters and can effectively represent a hazard rate function with a shape resembling a bathtub. Its significance in the fields of lifetime and reliability stems from its ability to model both increasing and decreasing failure rates. The p...

The problem of computing distances and shortest paths between vertices in graphs is one of the fundamental issues in graph theory. It is of great importance in many different applications, for example, transportation, and social network analysis. However, efficient shortest distance algorithms are still desired in many disciplines. Basically, the m...

The problem of computing distances and shortest paths between vertices in graphs is one of the fundamental issues in graph theory. It is of great importance in many different applications, for example, transportation, and social network analysis. However, efficient shortest distance algorithms are still desired in many disciplines. Basically, the m...