| uniroot.all {rootSolve} | R Documentation |
The function uniroot.all searches the interval from lower to upper for several roots (i.e., zero's) of a function f with respect to its first argument.
The number of roots found will depend on the number of subintervals in which the interval is subdivided
The function calls uniroot, the basic R-function.
uniroot.all(f, interval, lower=min(interval), upper=max(interval), tol=.Machine$double.eps^0.2, maxiter=1000, n=100, ...)
f |
the function for which the root is sought. |
interval |
a vector containing the end-points of the interval to be searched for the root. |
lower |
the lower end point of the interval to be searched. |
upper |
the upper end point of the interval to be searched. |
tol |
the desired accuracy (convergence tolerance). |
maxiter |
the maximum number of iterations. |
n |
number of subintervals in which the root is sought |
... |
additional named or unnamed arguments to be passed to f (but beware of partial matching to other arguments). |
f will be called as f(x, ...) for a numeric value of x.
Run demo(Jacobandroots) for an example of the use of uniroot.all for steady-state analysis.
See also second example of gradient
This example is discussed in the book by Soetaert and Herman (2008).
a vector with the roots found in the interval
It is not guaranteed that all roots will be recovered.
This will depend on n, the number of subintervals in which the interval is divided.
If the function "touches" the X-axis (i.e. the root is a saddle point), then this root will generally not be retrieved.
(but chances of this are pretty small).
Karline Soetaert <k.soetaert@nioo.knaw.nl>
uniroot for more information about input
##############################
## 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 pathetic 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(2008)
# 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 book of Soetaert and Herman")
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"))