covatree-class: A Reference Class for Search Tree Approximated Local...

In covafillr: Local Polynomial Regression of State Dependent Covariates in State-Space Models

Description

A Reference Class for Search Tree Approximated Local Polynomial Regression with covatree.

Fields

ptr

External pointer to the covatree C++ object

Methods

getDim()

Get the dimension of the coordinates.

initialize( coord, obs, h = suggestBandwith(coord, p), p = 3L, minLeft = length(obs)/10, ... )

Method to initialize the covafill. coord is a matrix of coordinates, obs is a vector of corresponding observations, h is a vector of bandwiths, p is the polynomial degree, and minLeft is the minimum number of observations that will create a sub tree.

predict(coord)

Predict function value and first order derivatives with search tree approximated local polynomial regression at coord.

Examples

getRefClass('covatree')
fn <- function(x) x ^ 4 - x ^ 2
x <- runif(2000,-3,3)
y <- fn(x) + rnorm(2000,0,0.1)
ct <- covatree(coord = x,obs = y,p = 5L, minLeft = 50)
ct$getDim()
x0 <- seq(-1,1,0.1)
y0 <- ct$predict(x0)
par(mfrow=c(2,1))
plot(x0,y0[,1], main = "Function")
lines(x0,fn(x0))
plot(x0, y0[,2], main = "First derivative")
lines(x0, 4 * x0 ^ 3 - 2 * x0)

covafillr documentation built on Dec. 1, 2019, 1:17 a.m.