Statistical Modelling

Exploring polynomial, fractional polynomial, and spline models

1 Polynomial models 2 Fractional polynomial models 2.1 Finding optimal power Values in fractional polynomials 3 Spline models 3.1 Example 3.2 Challenges 3.3 Selection process for spline models 4 Citation The ability to accurately model and interpret complex data sets is paramount. This technical exploration delves into three sophisticated modelling techniques: - Polynomial Models, - Fractional Polynomials, and - Spline Models. Each of these models serves as a fundamental tool in the statistical toolkit, enabling us to capture and understand the intricacies of linear and non-linear relationships inherent in real-world data.

Jan 19, 2024

Analysis of non-additive genetic variance in breeding programmes

Developed framework for temporal and genomic analysis of additive and dominance genetic variance

Feb 10, 2022

Modelling menstrual cycle length in athletes using state-space models

Development of an appropriate parametric state-space formulation for the marginal distribution of standard menstrual cycles for female athletes

Aug 20, 2021

Global Short-Term Forecasting of Covid-19 Cases

We show our model generates high accurate forecasts up to seven days ahead for COVID-19 reported cases.

Apr 6, 2021

Settling and feeding behavior of sharpshooter vectors on plum genotypes with different susceptibility levels to leaf scald disease (Xylella fastidiosa)

We focused to investigate the host non preference and suitability for xylem-sap feeding among plum genotypes that differ in bacterial leaf scald intensity in the field.

Aug 17, 2020