SScousens85 {statforbiology} | R Documentation |
Rectangular hyperbola for yield/weed density relationship
Description
These functions provide the rectangula hyperbola that was devided by Cousens (1985)
for modelling the relationship between crop yield and weed density. The function was
derived from the yield-loss function, and contains parameters that are revelant for
competition studies. These functions provide the
equation (cousens85.fun), the self-starters for the nls
function (NLS.cousens85) and the self-starters for
the drm
function in the drc package (DRC.cousens85)
Usage
cousens85.fun(predictor, Ywf, i, A)
NLS.cousens85(predictor, Ywf, i, A)
DRC.cousens85(fixed = c(NA, NA, NA), names = c("Ywf", "i", "A"))
Arguments
predictor |
a numeric vector of values at which to evaluate the model |
Ywf |
model parameter (Weed-free yield) |
i |
model parameter (initial slope) |
A |
model parameter (maximum percentage yield loss) |
fixed |
numeric vector. Specifies which parameters are fixed and at what value they are fixed. NAs for parameter that are not fixed. |
names |
a vector of character strings giving the names of the parameters. The default is usually reasonable. |
Details
This equation is parameterised as:
f(x) = Ywf \, \frac{(1 - (i predictor)} {(100 \, (1 + i \, predictor/A)))}
It depicts a decreasing curve with no inflection point. The curve is equal to 'Ywf' when x = 0 and the lower asymptote is at 'A' multiplied by 'Ywf/100'
Value
cousens85.fun, NLS.cousens85 return a numeric value, while DRC.cousens85 return a list containing the nonlinear function and the self starter function
Author(s)
Andrea Onofri
References
Ratkowsky, DA (1990) Handbook of nonlinear regression models. New York (USA): Marcel Dekker Inc.
Onofri, A. (2020). A collection of self-starters for nonlinear regression in R. See: https://www.statforbiology.com/2020/stat_nls_usefulfunctions/
Cousens, R., 1985. A simple model relating yield loss to weed density. Annals of Applied Biology 107, 239–252. https://doi.org/10.1111/j.1744-7348.1985.tb01567.x
Examples
library(statforbiology)
dataset <- getAgroData("Sinapis")
# nls fit
mod.nls <- nls(yield ~ NLS.cousens85(density, Ywf, i, A),
data = dataset )
summary(mod.nls)
mod.nls2 <- drm(yield ~ density, fct = DRC.cousens85(), data = dataset )
summary(mod.nls2)
plot(mod.nls2)