Opt(object, ...)
Coef
.Optima occur in quadratic and additive ordination, e.g., CQO or UQO or CAO. For these models the optimum is the value of the latent variable where the maximum occurs, i.e., where the fitted value achieves its highest value. For quadratic ordination models there is a formula for the optimum but for additive ordination models the optimum must be searched for numerically. If it occurs on the boundary, then the optimum is undefined. At an optimum, the fitted value of the response is called the maximum.
Yee, T. W. (2006) Constrained additive ordination. Ecology, 87, 203--213.
Opt.qrrvglm
,
Max
,
Tol
.set.seed(111) # This leads to the global solution
hspider[,1:6] = scale(hspider[,1:6]) # Standardized environmental vars
# vvv p1 = cqo(cbind(Alopacce, Alopcune, Alopfabr, Arctlute, Arctperi,
# vvv Auloalbi, Pardlugu, Pardmont, Pardnigr, Pardpull,
# vvv Trocterr, Zoraspin) ~
# vvv WaterCon + BareSand + FallTwig + CoveMoss + CoveHerb + ReflLux,
# vvv Bestof = 2,
# vvv fam = quasipoissonff, data = hspider, Crow1positive=FALSE)
# vvv Opt(p1)
index = 1:ncol(p1@y)
persp(p1, col=index, las=1, lwd=2, main="Vertical lines at the optima")
abline(v=Opt(p1), lty=2, col=index)
Run the code above in your browser using DataLab