goldensearch: Golden Section Search Algorithm
In estsyawo/cluscov: Clustered Covariate Regression
Description
Usage
Arguments
Value
Examples
Description
Minimising a continuous univariate function using the golden section search algorithm.
Usage
1
goldensearch(fn, interval, tol = 1)
Arguments
fn
the function; should be scalar valued
interval
a vector containing the lower and upper bounds of search
tol
tolerance level for convergence
Value
a list of objects
k: minimiser
value: mimimum value
iter: number of iterations before convergence
iterfn: number of function evaluations
Examples
1
fn = function(x) (x-1)^2; goldensearch(fn=fn,interval=c(-2,3),tol=1)
estsyawo/cluscov documentation built on June 9, 2019, 1:47 a.m.
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Description Usage Arguments Value Examples
Description
Minimising a continuous univariate function using the golden section search algorithm.
Usage
1 | goldensearch(fn, interval, tol = 1)
|
Arguments
fn |
the function; should be scalar valued |
interval |
a vector containing the lower and upper bounds of search |
tol |
tolerance level for convergence |
Value
a list of objects
k: minimiser
value: mimimum value
iter: number of iterations before convergence
iterfn: number of function evaluations
Examples
1 | fn = function(x) (x-1)^2; goldensearch(fn=fn,interval=c(-2,3),tol=1)
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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