drcte - Statistical Approaches for Time-to-Event Data in Agriculture
A specific and comprehensive framework for the analyses of time-to-event data in agriculture. Fit non-parametric and parametric time-to-event models. Compare time-to-event curves for different experimental groups. Plots and other displays. It is particularly tailored to the analyses of data from germination and emergence assays. The methods are described in Onofri et al. (2022) "A unified framework for the analysis of germination, emergence, and other time-to-event data in weed science", Weed Science, 70, 259-271 <doi:10.1017/wsc.2022.8>.
Last updated 1 years ago
non-linear-regressionseed-germinationtime-to-event
4.07 score 2 dependents 39 scripts 406 downloadsdrcSeedGerm - Utilities for Data Analyses in Seed Germination/Emergence Assays
Utility functions to be used to analyse datasets obtained from seed germination/emergence assays. Fits several types of seed germination/emergence models, including those reported in Onofri et al. (2018) "Hydrothermal-time-to-event models for seed germination", European Journal of Agronomy, 101, 129-139 <doi:10.1016/j.eja.2018.08.011>. Contains several datasets for practicing.
Last updated 2 months ago
nonlinear-regressionseed-germination-assaystime-to-event
3.97 score 5 stars 37 scripts 209 downloadslmDiallel - Linear Fixed/Mixed Effects Models for Diallel Crosses
Several service functions to be used to analyse datasets obtained from diallel experiments within the frame of linear models in R, as described in Onofri et al (2020) <DOI:10.1007/s00122-020-03716-8>.
Last updated 2 years ago
3.74 score 5 stars 22 scripts 233 downloads