# dy.dx: Partial Derivative dy/dx In OVVO-Financial/NNS: Nonlinear Nonparametric Statistics

## Description

Returns the numerical partial derivate of `y` wrt `x` for a point of interest.

## Usage

 ```1 2``` ```dy.dx(x, y, eval.point = median(x), deriv.order = 1, h = 0.05, deriv.method = "FS") ```

## Arguments

 `x` a numeric vector. `y` a numeric vector. `eval.point` numeric; `x` point to be evaluated. Defaults to `(eval.point = median(x))`. Set to `(eval.point = "overall")` to find an overall partial derivative estimate. `deriv.order` numeric options: (1, 2); 1 (default) for first derivative. For second derivative estimate of `f(x)`, set `(deriv.order = 2)`. `h` numeric [0, ...]; Percentage step used for finite step method. Defaults to `h = .05` representing a 5 percent step from the value of the independent variable. `deriv.method` method of derivative estimation, options: ("NNS", "FS"); Determines the partial derivative from the coefficient of the NNS.reg output when `(deriv.method = "NNS")` or generates a partial derivative using the finite step method `(deriv.method = "FS")` (Defualt).

## Value

Returns the value of the partial derivative estimate for the given order.

## Note

If a vector of derivatives is required, ensure `(deriv.method = "FS")`.

## Author(s)

Fred Viole, OVVO Financial Systems

## References

Viole, F. and Nawrocki, D. (2013) "Nonlinear Nonparametric Statistics: Using Partial Moments" https://www.amazon.com/dp/1490523995

Vinod, H. and Viole, F. (2017) "Nonparametric Regression Using Clusters" https://link.springer.com/article/10.1007/s10614-017-9713-5

## Examples

 ```1 2 3 4 5 6 7``` ```## Not run: x <- seq(0, 2 * pi, pi / 100) ; y <-sin(x) dy.dx(x, y, eval.point = 1.75) # Vector of derivatives dy.dx(x, y, eval.point = c(1.75, 2.5), deriv.method = "FS") ## End(Not run) ```

OVVO-Financial/NNS documentation built on Feb. 14, 2020, 8:16 a.m.