Description Usage Arguments Details Value See Also Examples
Use gradient descent to find local minima
1 2 3 4 5 |
fp |
function representing the derivative of |
x |
an initial estimate of the minima |
h |
the step size |
tol |
the error tolerance |
m |
the maximum number of iterations |
Gradient descent can be used to find local minima of functions. It
will return an approximation based on the step size h
and
fp
. The tol
is the error tolerance, x
is the
initial guess at the minimum. This implementation also stops after
m
iterations.
the x
value of the minimum found
Other optimz:
bisection()
,
goldsect
,
hillclimbing()
,
newton()
,
sa()
,
secant()
1 2 3 4 5 6 7 8 9 10 11 |
[1] 0.5067967
[1] 0.9991405 1.0000000
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