pricefit {ecolMod}R Documentation

Pseudo-random search algorithm of Price (1997)

Description

Pseudo-random search algorithm of Price (1997). Used in the book as an example of a random-based fitting technique, and as an example of how to create a function in R.

Usage

pricefit(par, minpar=rep(-1e8,length(par)),
maxpar=rep(1e8,length(par)), func, npop=max(5*length(par),50),
numiter=10000, centroid = 3, varleft  = 1e-8,...)

Arguments

par initial values of the parameters to be optimised
minpar minimal values of the parameters to be optimised
maxpar maximal values of the parameters to be optimised
func function to be minimised, its first argument should bw the vector of parameters over which minimization is to take place. It should return a scalar result, the model cost, e.g the sum of squared residuals.
npop number of elements in population
numiter number of iterations to be performed. Defaults to 10000. There is no other stopping criterion.
centroid number of elements from which to estimate new parameter vector
varleft relative variation remaining; if below this value algorithm stops
... arguments passed to funtion func

Details

see the book of Soetaert and Herman for a description of the algorithm AND for a line to line explanation of the function code.

Value

a list containing:

par the optimised parameter values
cost the model cost, or function evaluation associated to the optimised parameter values, i.e. the minimal cost
poppar all parameter vectors remaining in the population, matrix of dimension (npop,length(par))
popcost model costs associated with all population parameter vectors, vector of length npop

Author(s)

Karline Soetaert <k.soetaert@nioo.knaw.nl>

References

Soetaert, K. and P.M.J. Herman, 2009. A Practical Guide to Ecological Modelling. Using R as a Simulation Platform. Springer, 372 pp.

Price, W.L., 1977. A controlled random search procedure for global optimisation. The Computer Journal, 20: 367-370.

See Also

optim the R default.

Examples

pricefit  # will display the code 

amp    <- 6
period <- 5
phase  <- 0.5

x <- runif(20)*13 
y <- amp*sin(2*pi*x/period+phase) +rnorm(20,mean=0,sd=0.05)
plot(x,y,pch=16)

cost <- function(par) sum((par[1]*sin(2*pi*x/par[2]+par[3])-y)^2)

p1 <- optim(par=c(amplitude=1,phase=1,period=1), cost)
p2 <- optim(par=c(amplitude=1,phase=1,period=1), cost,method="SANN")
p3 <- pricefit(par=c(amplitude=1,phase=1,period=1),minpar=c(0,1e-8,0),
               maxpar=c(100,2*pi,100), func=cost,numiter=3000)

curve(p1$par[1]*sin(2*pi*x/p1$par[2]+p1$par[3]),lty=2,add=TRUE)
curve(p2$par[1]*sin(2*pi*x/p2$par[2]+p2$par[3]),lty=3,add=TRUE)
curve(p3$par[1]*sin(2*pi*x/p3$par[2]+p3$par[3]),lty=1,add=TRUE)
legend ("bottomright",lty=c(1,2,3),c("Price","Mathematical","Simulated annealing"))

[Package ecolMod version 1.2.1 Index]