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The “Models” that are part of the regression namespace are kind of like classed versions of closures. We could create a parent object which includes a simple derivative() function, which could be overridden by a child if the child had a simple derivative. This accurate derivative could be used in the root-finding algorithm instead of the estimate.
The text was updated successfully, but these errors were encountered:
For PowerModel, for instance, there would be a derivative method that returned a function that would evaluate ab * xᵇ⁻¹ based on what a and b were already set to, taking only x as a parameter I presume.
If performing root-finding, Newton’s method would only need (∂y / ∂x), but for nonlinear least squares, there would need to be (∂y / ∂a) and (∂y / ∂b).
The “Models” that are part of the regression namespace are kind of like classed versions of closures. We could create a parent object which includes a simple
derivative()
function, which could be overridden by a child if the child had a simple derivative. This accurate derivative could be used in the root-finding algorithm instead of the estimate.The text was updated successfully, but these errors were encountered: