Recent & Upcoming Talks

Quantifying the Drivers of Genetic Change in Plant Breeding

Evaluate the contribution of germplasm origin given the heterotic pool in a maize breeding programme into contributions to additive genetic mean and variance summarized over the years

Sep 21, 2022

A method for partitioning trends in genetic mean and variance to understand breeding practices

Partitioning method to quantify the contribution of different groups to genetic variance and its impact in breeding programme

Jul 27, 2022

Visualization and Data Structure

Discussion on the principles of grammar of graphics and tidy data with application using the tidyverse

Sep 20, 2021

Global Short-Term Forecasting of Covid-19 Cases

Accurate short-term forecasting is thus vital to support country-level policy making during COVID-19 outbreak

Nov 12, 2020

Global Short-Term Forecasting of Covid-19 Cases

Accurate short-term forecasting is thus vital to support country-level policy making during COVID-19 outbreak

Jun 1, 2020

Estimating NBA athlete performance using multilevel models

Athlete performance evaluation based on novel methodology using principal components and multilevel models

Apr 21, 2020

Modelling menstrual cycle length using state space models

Times are changing. At an elite level, female athletes and coaches across the globe are now starting to work with the menstrual cycle to gain a performance edge. By tracking the menstrual cycle, and knowing how, why and when hormone fluctuations affect female physiology, an athlete's training, nutrition and recovery can be tailored to their cycle to sustain peak performance

Oct 4, 2019

The longitudinal concordance correlation

Abstract: We present the lcc package, available from the Comprehensive R Archive Network (CRAN). The package implements estimation procedures for the longitudinal concordance correlation (LCC), using fixed effects and variance components estimates from linear mixed models.

Jun 7, 2019