Longitudinal data are valuable in various disciplines because they provide helpful developmental patterns over time. However, frequently, it is challenging to have a high dimension of covariates and ubiquitous missing ...

Generalized distributions have become widely used in applications recently. They are very flexible in data analysis, especially with skewed models that are important and occur frequently in many applications. In particular, ...

Several diagnostic tests for the lack of fit time series models have been introduced using parametric and nonparametric portmanteau tests. Some tests have been proposed based on the asymptotic distributions. Others are ...

In this thesis, we consider improving maximum likelihood inference for the scale parameter of the Lomax distribution. The improvement is based on using modification to the maximum likelihood estimator based on Barndorff-Nielsen's ...

In this thesis, we utilize quantile regression to model the conditional quantile of the dependent variable given independent variables to capture more details about the conditional distribution. In addition, we apply the ...

In recent years neuroimaging techniques growth help us to understand the working of the human brain by using structural magnetic resonance imaging (sMRI) and functional magnetic resonance imaging (fMRI). Structural MRIs ...

COVID-19 pandemic has led to the lockdown of major cities worldwide, which caused the early closure of schools and educational institutions in the towns affected. This pandemic had a negative impact on the performance of ...

Generally, survival analysis is a significant aspect of statistics that helps in anticipating possible outcomes in the various phenomena of study. A competing risk model is widely used in survival analysis since it not ...

Exploring the statistical association between more than two variables requires utilizing a proper technique/test along with meeting its required assumptions. Measures of correlation are used to explain such associations ...