findmins.RdFinding all local(!) minima of a unvariate function in an interval by splitting the interval in many small subintervals.
findmins(f, a, b, n = 100, tol = .Machine$double.eps^(2/3), ...)Local minima are found by looking for one minimum in each subinterval.
It will be found by applying optimize to any two adjacent
subinterval where the first slope is negative and the second one
positive.
If the function is minimal on a whole subinterval, this will cause problems. If some minima are apparently not found, increase the number of subintervals.
Note that the endpoints of the interval will never be considered to be local minima. The function need not be vectorized.
Numeric vector with the x-positions of all minima found in the interval.
fun <- function(x) x * cos(0.1*exp(x)) * sin(0.1*pi*exp(x))
if (FALSE) ezplot(fun, 0, 5, n = 1001) # \dontrun{}
# If n is smaller, the rightmost minimum will not be found.
findmins(fun, 0, 5, n= 1000)
#> [1] 2.537727 3.248481 3.761840 4.023021 4.295831 4.455115 4.641481 4.756263
#> [9] 4.897461 4.987802
# 2.537727 3.248481 3.761840 4.023021 4.295831
# 4.455115 4.641481 4.756263 4.897461 4.987802