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ON VARIABLE SELECTION WITH THE PRESENCE OF MISSING DATA IN LONGITUDINAL PANEL STUDIES
(Applied Statistics, 06-2 , Master Thesis)
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 ...
LINEAR AND BAYESIAN ESTIMATION OF THE PARAMETERS OF THE TYPE II GENERALIZED LOGISTIC DISTRIBUTION BASED ON PROGRESSIVELY TYPE II CENSORED DATA
(Applied Statistics, 06-2 , Master Thesis)
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, ...
PARAMETRIC AND NONPARAMETRIC PORTMANTEAU TESTS FOR LACK OF FIT IN TIME SERIES MODELS: A COMPARATIVE STUDY
(Applied Statistics, 06-2 , Master Thesis)
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 ...
IMPROVED INFERENCE FOR THE SCALE PARAMETER IN THE LOMAX DISTRIBUTION BASED ON ADJUSTED PROFILE LIKELIHOOD FUNCTIONS
(Applied Statistics, 06-2 , Master Thesis)
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 ...
NON-DETERMINISTIC MODELING USING QUANTILE REGRESSION
(Applied Statistics, 06-2 , Master Thesis)
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 ...
VARIOGRAM MODELING FOR SPATIAL CORRELATION IN STRUCTURAL MRI IMAGES
(Applied Statistics, 06-2 , Master Thesis)
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 ...
COMPETING RISKS MODEL BASED ON FINE AND GRAY IN PRESENCE OF INTERVAL CENSORED DATA
(Applied Statistics, 2022 , Master Thesis)
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 ...
Likelihood Inference for Step Stress Partially Accelerated Life Test Model with Type I Progressively Hybrid Censored Data from Generalized Exponential Distribution
(Applied Statistics, 2021 , Master Thesis)
This thesis considers the statistical inference on the generalized exponential
distribution parameters in presence of progressive Type-I censoring under partially
accelerated life test. The maximum likelihood method ...
Cumulative exposure lognormal model with hybrid
(Applied Statistics, 2021 , Master Thesis)
This research aims to analyze data coming from step stress life testing experiments that
are commonly used to make inferences on the reliability of products and machines.
Customers expect a reliable product that can ...
ON THE PREFERENCE OF ZERO-INFLATION MODELS WITH THE PRESENCE OF DATA CONTAMINATION
(Applied Statistics, 2023 , Master Thesis)
Nowadays, data has become a big concern for researchers to solve problems or improve a lifestyle. It is not odd that different data sources generate data with different characters. In fields such as engineering, epidemiology, ...