findmins(f, a, b, n = 100, tol = .Machine$double.eps^(2/3), ...)
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.
optimize
fun <- function(x) x * cos(0.1*exp(x)) * sin(0.1*pi*exp(x))
ezplot(fun, 0, 5, n = 1001)
# If n is smaller, the rightmost minimum will not be found.
findmins(fun, 0, 5, n= 1000)
# 2.537727 3.248481 3.761840 4.023021 4.295831
# 4.455115 4.641481 4.756263 4.897461 4.987802
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