FStat {HTSeedGLM} | R Documentation |
F-test between two fitted models
Description
This function considers two fitted models as inputs. Considering the first model as full model, it performs testing equality of uniformity parameters representing the model under null hypothesis and provides the p-value and degrees of freedom of the test statistic.
Usage
FStat(model1, model2)
Arguments
model1 |
First fitted model |
model2 |
Second fitted model |
Value
Degrees of freedom and p-value
References
Bradford, K. J. (2002). Applications of Hydrothermal Time to Quantifying and Modeling Seed Germination and Dormancy. Weed Science, 50(2), 248–260. http://www.jstor.org/stable/4046371
Kebreab, E., & Murdoch, A. J. (1999). Modelling the effects of water stress and temperature on germination rate of Orobanche aegyptiaca seeds. Journal of Experimental Botany, 50(334), 655-664. doi:10.1093/jxb/50.334.655
Dobson, A. J., & Barnett, A. G. (2018). An introduction to generalized linear models. Chapman and Hall/CRC.
Examples
data1 <- data.frame(cbind(sg = c(rep(1, 95), rep(0, 5), rep(1, 87), rep(0, 13),
rep(1, 80), rep(0, 20), rep(1, 59), rep(0, 41),
rep(1, 50), rep(0, 50), rep(1, 79), rep(0, 21),
rep(1, 69), rep(0, 31), rep(1, 72), rep(0, 28),
rep(1, 44), rep(0, 56), rep(1, 14), rep(0, 86)),
v1 = c(rep(1, 500), rep(0, 500)),
v2 = c(rep(0, 500), rep(1, 500)),
wp1 = c(rep(0, 100), rep(-0.3, 100), rep(-0.6, 100),
rep(-0.9, 100), rep(-1.2, 100), rep(0, 500)),
wp2 = c(rep(0, 600), rep(-0.3, 100), rep(-0.6, 100),
rep(-0.9, 100), rep(-1.2, 100))))
data2 <- data.frame(cbind(sg = c(rep(1, 95), rep(0, 5), rep(1, 87), rep(0, 13),
rep(1, 80), rep(0, 20), rep(1, 59), rep(0, 41),
rep(1, 50), rep(0, 50), rep(1, 79), rep(0, 21),
rep(1, 69), rep(0, 31), rep(1, 72), rep(0, 28),
rep(1, 44), rep(0, 56), rep(1, 14), rep(0, 86)),
v1 = c(rep(1, 500), rep(0, 500)),
v2 = c(rep(0, 500), rep(1, 500)),
wp = c(rep(0, 100), rep(-0.3, 100), rep(-0.6, 100),
rep(-0.9, 100), rep(-1.2, 100), rep(0, 100),
rep(-0.3, 100), rep(-0.6, 100), rep(-0.9, 100),
rep(-1.2, 100))))
myprobit1 <- glm(sg ~ v1 + v2 + wp1 + wp2 - 1, data = data1, family = binomial(link = probit))
myprobit2 <- glm(sg ~ v1 + v2 + wp - 1, data = data2,
family = binomial(link = probit))
my.f<- FStat(myprobit1, myprobit2)