maxcurv {soilphysics} | R Documentation |
Maximum Curvature Point
Description
Function to determine the maximum curvature point of an univariate nonlinear function of x.
Usage
maxcurv(x.range, fun,
method = c("general", "pd", "LRP", "spline"),
x0ini = NULL,
graph = TRUE, ...)
Arguments
x.range |
a numeric vector of length two, the range of x. |
fun |
a function of x; it must be a one-line-written function, with no curly braces '{}'. |
method |
a character indicating one of the following: "general" - for evaluating the general curvature function (k), "pd" - for evaluating perpendicular distances from a secant line, "LRP" - a NLS estimate of the maximum curvature point as the breaking point of Linear Response Plateau model, "spline" - a NLS estimate of the maximum curvature point as the breaking point of a piecewise linear spline. See details. |
x0ini |
an initial x-value for the maximum curvature point. Required only when "LRP" or "spline" are used. |
graph |
logical; if TRUE (default) a curve of |
... |
further graphical arguments. |
Details
The method "LRP" can be understood as an especial case of "spline". And both models are fitted via nls
.
The method "pd" is an adaptation of the method proposed by Lorentz et al. (2012). The "general" method should be
preferred for finding global points. On the other hand, "pd", "LRP" and "spline" are suitable for finding
local points of maximum curvature.
Value
A list of
fun |
the function of x. |
x0 |
the x critical value. |
y0 |
the y critical value. |
method |
the method of determination (input). |
Author(s)
Anderson Rodrigo da Silva <anderson.agro@hotmail.com>
References
Lorentz, L.H.; Erichsen, R.; Lucio, A.D. (2012). Proposal method for plot size estimation in crops. Revista Ceres, 59:772–780.
See Also
Examples
# Example 1: an exponential model
f <- function(x) exp(-x)
maxcurv(x.range = c(-2, 5), fun = f)
# Example 2: Gompertz Growth Model
Asym <- 8.5
b2 <- 2.3
b3 <- 0.6
g <- function(x) Asym * exp(-b2 * b3 ^ x)
maxcurv(x.range = c(-5, 20), fun = g)
# using "pd" method
maxcurv(x.range = c(-5, 20), fun = g, method = "pd")
# using "LRP" method
maxcurv(x.range = c(-5, 20), fun = g, method = "LRP", x0ini = 6.5)
# Example 3: Lessman & Atkins (1963) model for optimum plot size
a = 40.1
b = 0.72
cv <- function(x) a * x^-b
maxcurv(x.range = c(1, 50), fun = cv)
# using "spline" method
maxcurv(x.range = c(1, 50), fun = cv, method = "spline", x0ini = 6)
# End (not run)