choice.grid: Choice of the quantization grids

In QuantifQuantile: Estimation of Conditional Quantiles using Optimal Quantization

Description

This function provides ng optimal quantization grids for X, with N fixed.

Usage

choice.grid(X, N, ng = 1, p = 2)

Arguments

X	vector or matrix that we want to quantize.
N	size of the quantization grids.
ng	number of quantization grids needed.
p	L_p norm optimal quantization.

Details

This function works for any dimension of X. If the covariate is univariate, X is a vector while X is a matrix with d rows when the covariate is d-dimensional.

Value

An array of dimension d*N*ng that corresponds to ng quantization grids.

References

Charlier, I. and Paindaveine, D. and Saracco, J., Conditional quantile estimator based on optimal quantization: from theory to practice, Submitted.

Pages, G. (1998) A space quantization method for numerical integration, Journal of Computational and Applied Mathematics, 89(1), 1-38

See Also

QuantifQuantile, QuantifQuantile.d2 and QuantifQuantile.d

Examples

X <- runif(300,-2,2)
N <- 10
ng <- 20
choice.grid(X,N,ng)

QuantifQuantile documentation built on May 2, 2019, 2:10 a.m.