Description Usage Arguments Details Value Author(s) References See Also Examples

Function to determine the maximum curvature point of an univariate nonlinear function of x.

1 2 3 4 |

`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 ( |

`x0ini` |
an initial |

`graph` |
logical; if TRUE (default) a curve of |

`...` |
further graphical arguments. |

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.

A list of

`fun` |
the function of x. |

`x0` |
the x critical value. |

`y0` |
the y critical value. |

`method` |
the method of determination (input). |

Anderson Rodrigo da Silva <[email protected]>

Lorentz, L.H.; Erichsen, R.; Lucio, A.D. (2012). Proposal method for plot size estimation in crops.
*Revista Ceres*, 59:772–780.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | ```
# 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)
``` |

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