yieldLoss: Calculating yield loss parameters

In MaximeBSanofi/drc2:

Description

Calculation of parameters in the re-parameterization of the Michaelis-Menten model that is commonly used to assess yield loss (the rectangular hyperbola model)

Usage

  yieldLoss(object, interval = c("none", "as"), level = 0.95, display = TRUE)

Arguments

object	object of class 'drc
interval	character string specifying the type of confidence intervals to be supplied. The default is "none". Use "as" for asymptotically-based confidence intervals.
level	numeric. The level for the confidence intervals. The default is 0.95.
display	logical. If TRUE results are displayed. Otherwise they are not (useful in simulations).

Details

The rectangular hyperbola model is a reparameterization of the Michaelis-Menten in terms of parameters A and I

Y_L = \frac{Id}{1+Id/A}

where d denotes the weed density and Y_L the resulting yield loss.

Value

For each of the two parameters, a matrix with two or more columns, containing the estimates and the corresponding estimated standard errors and possibly lower and upper confidence limits.

Note

This function is only for use with model fits based on Michaelis-Menten models.

Author(s)

Christian Ritz

References

Cousens, R. (1985). A simple model relating yield loss to weed density, Ann. Appl. Biol., 107, 239–252.

Examples

## Fitting Michaelis-Menten model
met.mm.m1 <- drm(gain~dose, product, data = methionine, fct = MM.3(), 
pmodels = list(~1, ~factor(product), ~factor(product)))

## Yield loss parameters with standard errrors
yieldLoss(met.mm.m1)

## Also showing confidence intervals
yieldLoss(met.mm.m1, "as")

MaximeBSanofi/drc2 documentation built on Feb. 22, 2022, 12:02 a.m.