# covafill-class: A Reference Class for Local Polynomial Regression with... In covafillr: Local Polynomial Regression of State Dependent Covariates in State-Space Models

## Description

A Reference Class for Local Polynomial Regression with covafill.

## Fields

`ptr`

External pointer to the covafill C++ object

## Methods

`getBandwith()`

Get the bandwith.

`getDegree()`

Get the polynomial degree.

`getDim()`

Get the dimension of the coordinates.

`initialize(coord, obs, h = suggestBandwith(coord, p), p = 3L, ...)`

Method to initialize the covafill. coord is a matrix of coordinates, obs is a vector of corresponding observations, h is a vector of bandwiths, and p is the polynomial degree.

`predict(coord, se.fit = FALSE)`

Predict function value and derivatives with local polynomial regression at coord. If se.fit=TRUE a list is returned with estimates and their standard deviations.

`residuals(excludeRadius)`

Get 'leave-neighborhood-out' residuals, i.e. local polynomial regression predictions excluding points within excludeRadius subtracted from the observation.

`setBandwith(h)`

Set the bandwith to h.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19``` ```getRefClass('covafill') fn <- function(x) x ^ 4 - x ^ 2 x <- runif(2000,-3,3) y <- fn(x) + rnorm(2000,0,0.1) cf <- covafill(coord = x,obs = y,p = 5L) cf\$getDim() cf\$getDegree() cf\$getBandwith() x0 <- seq(-1,1,0.1) y0 <- cf\$predict(x0) par(mfrow=c(3,1)) plot(x0,y0[,1], main = "Function") lines(x0,fn(x0)) plot(x0, y0[,2], main = "First derivative") lines(x0, 4 * x0 ^ 3 - 2 * x0) plot(x0, y0[,3], main = "Second derivative") lines(x0, 3 * 4 * x0 ^ 2 - 2) cf\$setBandwith(1.0) cf\$getBandwith() ```

covafillr documentation built on Nov. 20, 2017, 5:08 p.m.