Vertaile menetelmiä
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| Itämiskineettinen mallinnus× | Selviytymisanalyysi× | |
|---|---|---|
| Tieteenala≠ | Agronomia | Tutkimuksen tilastomenetelmät |
| Menetelmäperhe | Process / pipeline | Process / pipeline |
| Syntyvuosi≠ | 1970s–1990s (formalized thermal and hydrothermal time frameworks) | 1958 |
| Kehittäjä≠ | Multiple contributors (Hegarty 1973; Garcia-Huidobro et al. 1982; Bradford 1990) | Edward L. Kaplan and Paul Meier |
| Tyyppi≠ | Quantitative modeling / biophysical analysis | Method |
| Alkuperäislähde≠ | Bradford, K. J. (2002). Applications of hydrothermal time to quantifying and modeling seed germination and dormancy. Weed Science, 50(2), 248–260. DOI ↗ | Kaplan, E. L., & Meier, P. (1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53(282), 457–481. DOI ↗ |
| Rinnakkaisnimet≠ | seed germination modeling, thermal germination analysis, germination rate modeling, hydrothermal time modeling | Kaplan-Meier analysis, Cox regression, TTE analysis |
| Liittyvät≠ | 1 | 3 |
| Tiivistelmä≠ | Germination Kinetics Modeling is a quantitative method used in agronomy, seed science, and crop physiology to describe, predict, and compare the speed and uniformity of seed germination under varying environmental conditions. It draws on thermal time and hydrothermal time frameworks to link temperature, water potential, and time into biologically interpretable parameters, enabling researchers and agronomists to characterize seed lot quality and optimize planting conditions. | Survival analysis is a collection of statistical methods for modeling time from a defined starting point until an event of interest occurs (disease, recovery, death, equipment failure). Kaplan and Meier's nonparametric estimator (1958) and David Cox's proportional hazards model (1972) jointly enabled analysis of censored data—individuals whose event times are unknown because they left the study or were still event-free at follow-up. Indispensable in oncology, cardiology, infectious disease research, engineering reliability, and any field where time-to-event matters. |
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