Learn R Programming

VGAM (version 1.1-1)

Opt: Optimums

Description

Generic function for the optimums (or optima) of a model.

Usage

Opt(object, ...)

Arguments

object

An object for which the computation or extraction of an optimum (or optimums) is meaningful.

Other arguments fed into the specific methods function of the model. Sometimes they are fed into the methods function for Coef.

Value

The value returned depends specifically on the methods function invoked.

Details

Different models can define an optimum in different ways. Many models have no such notion or definition.

Optimums occur in quadratic and additive ordination, e.g., CQO 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.

References

Yee, T. W. (2004) A new technique for maximum-likelihood canonical Gaussian ordination. Ecological Monographs, 74, 685--701.

Yee, T. W. (2006) Constrained additive ordination. Ecology, 87, 203--213.

See Also

Opt.qrrvglm, Max, Tol.

Examples

Run this code
# NOT RUN {
set.seed(111)  # This leads to the global solution
hspider[,1:6] <- scale(hspider[,1:6])  # Standardized environmental vars
p1 <- cqo(cbind(Alopacce, Alopcune, Alopfabr, Arctlute, Arctperi,
                Auloalbi, Pardlugu, Pardmont, Pardnigr, Pardpull,
                Trocterr, Zoraspin) ~
          WaterCon + BareSand + FallTwig + CoveMoss + CoveHerb + ReflLux,
          family = poissonff, data = hspider, Crow1positive = FALSE)
Opt(p1)

# }
# NOT RUN {
clr <- (1:(ncol(depvar(p1))+1))[-7]  # Omits yellow
persp(p1, col = clr, las = 1, main = "Vertical lines at the optimums")
abline(v = Opt(p1), lty = 2, col = clr)
# }

Run the code above in your browser using DataLab