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Full-Text Articles in Statistical Models
Stressor: An R Package For Benchmarking Machine Learning Models, Samuel A. Haycock
Stressor: An R Package For Benchmarking Machine Learning Models, Samuel A. Haycock
All Graduate Theses and Dissertations, Spring 1920 to Summer 2023
Many discipline specific researchers need a way to quickly compare the accuracy of their predictive models to other alternatives. However, many of these researchers are not experienced with multiple programming languages. Python has recently been the leader in machine learning functionality, which includes the PyCaret library that allows users to develop high-performing machine learning models with only a few lines of code. The goal of the stressor package is to help users of the R programming language access the advantages of PyCaret without having to learn Python. This allows the user to leverage R’s powerful data analysis workflows, while simultaneously …
Novel Statistical Models For Quantitative Shape-Gene Association Selection, Xiaotian Dai
Novel Statistical Models For Quantitative Shape-Gene Association Selection, Xiaotian Dai
All Graduate Theses and Dissertations, Spring 1920 to Summer 2023
Other research reported that genetic mechanism plays a major role in the development process of biological shapes. The primary goal of this dissertation is to develop novel statistical models to investigate the quantitative relationships between biological shapes and genetic variants. However, these problems can be extremely challenging to traditional statistical models for a number of reasons: 1) the biological phenotypes cannot be effectively represented by single-valued traits, while traditional regression only handles one dependent variable; 2) in real-life genetic data, the number of candidate genes to be investigated is extremely large, and the signal-to-noise ratio of candidate genes is expected …
Simulation Of Mathematical Models In Genetic Analysis, Dinesh Govindal Patel
Simulation Of Mathematical Models In Genetic Analysis, Dinesh Govindal Patel
All Graduate Theses and Dissertations, Spring 1920 to Summer 2023
In recent years a new field of statistics has become of importance in many branches of experimental science. This is the Monte Carlo Method, so called because it is based on simulation of stochastic processes. By stochastic process, it is meant some possible physical process in the real world that has some random or stochastic element in its structure. This is the subject which may appropriately be called the dynamic part of statistics or the statistics of "change," in contrast with the static statistical problems which have so far been the more systematically studied. Many obvious examples of such processes …