growth.ac.cond: Conditional Autocatlytic Growth: Iterating differential...

In FredHasselman/nlRtsa: nonlineaR time seRies analysis.

Description

Conditional Autocatlytic Growth: Iterating differential equations (maps)

Usage

growth.ac.cond(Y0 = 0.01, r = 0.1, k = 2, cond = cbind.data.frame(Y =
  0.2, par = "r", val = 2), N = 100)

Arguments

Y0	Initial value
r	Growth rate parameter
k	Carrying capacity
cond	Conditional rules passed as a data.frame of the form: cbind.data.frame(Y = ..., par = ..., val = ...)
N	Length of the time series

Author(s)

Fred Hasselman

See Also

Other autocatalytic growth functions: growth.ac

Examples

# Plot with the default settings
xyplot(growth.ac.cond())

# The function such that it can take a set of conditional rules and apply them sequentially during the iterations.
# The conditional rules are passed as a `data.frame`
(cond <- cbind.data.frame(Y = c(0.2, 0.6), par = c("r", "r"), val = c(0.5, 0.1)))
xyplot(growth.ac.cond(cond=cond))

# Combine a change of `r` and a change of `k`
(cond <- cbind.data.frame(Y = c(0.2, 1.99), par = c("r", "k"), val = c(0.5, 3)))
xyplot(growth.ac.cond(cond=cond))

# A fantasy growth process
(cond <- cbind.data.frame(Y = c(0.1, 1.99, 1.999, 2.5, 2.9), par = c("r", "k", "r", "r","k"), val = c(0.3, 3, 0.9, 0.1, 1.3)))
xyplot(growth.ac.cond(cond=cond))

FredHasselman/nlRtsa documentation built on May 6, 2019, 5:07 p.m.