Search
Now showing items 21-30 of 31
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, ...
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 ...
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 ...
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 ...
Reliability analysis of the Stress-Strength model from truncated Pareto distribution based on progressive Type-II censored samples.
(Applied Statistics, 2023 , Professional Masters Project)
In this project, we studied the stress strength reliability (SSR) models. The stress-strength model has many applications in engineering problems, for example the strength of a building being subjected to earthquake, the ...
IMPLEMENTATION OF MACHINE LEARNING ALGORITHMS FOR CLASSIFICATION OF BONE MINERAL DENSITY TYPES BASED ON QATAR BIOBANK DATA
(Applied Statistics, 2023 , Master Thesis)
Bone Mineral Density (BMD) test measures the amount of calcium and other minerals in specific areas of bone. Low BMD is a well-known problem and results in bone fractures in millions of people around the world. BMD can be ...
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, ...
VOLATILITY ESTIMATION IN MISSING AT RANDOM HIGH-FREQUENCY FINANCIAL TIME SERIES
(Applied Statistics, 2023 , Master Thesis)
More than 15 years ago, the capital markets have seen significant development, introducing high-frequency trading and a shift of market towards high-frequency and algorithm trading. It was always believed that high-frequency ...