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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, ...
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 ...
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 ...
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 ...
Assessment and Prediction of Body Fat Composition Using A Variety of Machine Learning Algorithms
(Applied Sciences, 2023 , Master Thesis)
Body composition is critical for health outcomes and has been researched in various populations and conditions like obesity, diabetes, and many more. Qatar Biobank collected anthropometric and biomedical data from individuals ...