## =======================================================================
## Mathematical examples
## =======================================================================
# a well-behaved case...
fun <- function (x) cos(2*x)^3
curve(fun(x), 0, 10,main = "uniroot.all")
All <- uniroot.all(fun, c(0, 10))
points(All, y = rep(0, length(All)), pch = 16, cex = 2)
# a difficult case...
f <- function (x) 1/cos(1+x^2)
AA <- uniroot.all(f, c(-5, 5))
curve(f(x), -5, 5, n = 500, main = "uniroot.all")
points(AA, rep(0, length(AA)), col = "red", pch = 16)
f(AA) # !!!
## =======================================================================
## Ecological modelling example
## =======================================================================
# Example from the book of Soetaert and Herman(2009)
# A practical guide to ecological modelling -
# using R as a simulation platform. Springer
r <- 0.05
K <- 10
bet <- 0.1
alf <- 1
# the model : density-dependent growth and sigmoid-type mortality rate
rate <- function(x, r = 0.05) r*x*(1-x/K) - bet*x^2/(x^2+alf^2)
# find all roots within the interval [0,10]
Eq <- uniroot.all(rate, c(0, 10))
# jacobian evaluated at all roots:
# This is just one value - and therefore jacobian = eigenvalue
# the sign of eigenvalue: stability of the root: neg=stable, 0=saddle, pos=unstable
eig <- vector()
for (i in 1:length(Eq))
eig[i] <- sign (gradient(rate, Eq[i]))
curve(rate(x), ylab = "dx/dt", from = 0, to = 10,
main = "Budworm model, roots",
sub = "Example from Soetaert and Herman, 2009")
abline(h = 0)
points(x = Eq, y = rep(0, length(Eq)), pch = 21, cex = 2,
bg = c("grey", "black", "white")[eig+2] )
legend("topleft", pch = 22, pt.cex = 2,
c("stable", "saddle", "unstable"),
col = c("grey", "black", "white"),
pt.bg = c("grey", "black", "white"))
## =======================================================================
## Vectorisation:
## =======================================================================
# from R-help Digest, Vol 130, Issue 27
#https://stat.ethz.ch/pipermail/r-help/2013-December/364799.html
integrand1 <- function(x) 1/x*dnorm(x)
integrand2 <- function(x) 1/(2*x-50)*dnorm(x)
integrand3 <- function(x, C) 1/(x+C)
res <- function(C) {
integrate(integrand1, lower = 1, upper = 50)$value +
integrate(integrand2, lower = 50, upper = 100)$value -
integrate(integrand3, C = C, lower = 1, upper = 100)$value
}
# uniroot passes one value at a time to the function, so res can be used as such
uniroot(res, c(1, 1000))
# Need to vectorise the function to use uniroot.all:
res <- Vectorize(res)
uniroot.all(res, c(1,1000))
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