quant: Estimates the quantiles at a vector of probability values

Description Usage Arguments Value Examples

View source: R/hermite_estimator.R

Description

This method utilizes the estimator (13) in paper Stephanou, Michael, Varughese, Melvin and Iain Macdonald. "Sequential quantiles via Hermite series density estimation." Electronic Journal of Statistics 11.1 (2017): 570-607 <doi:10.1214/17-EJS1245>, with some modifications to improve the stability of numerical root finding. Note that this method is only applicable to the univariate Hermite estimator i.e. est_type = "univariate".

Usage

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quant(this, p, algorithm = "interpolate", accelerate_series = TRUE)

Arguments

this

A hermite_estimator_univar object.

p

A numeric vector. A vector of probability values.

algorithm

A string. Two possible values 'interpolate' which is faster but may be less accurate or 'bisection' which is slower but potentially more accurate.

accelerate_series

A boolean value. If set to TRUE, the series acceleration methods described in:

Boyd, John P., and Dennis W. Moore. "Summability methods for Hermite functions." Dynamics of atmospheres and oceans 10.1 (1986): 51-62.

are applied. If set to FALSE, then standard summation is applied.

Value

A numeric vector. The vector of quantile values associated with the probabilities p.

Examples

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hermite_est <- hermite_estimator(N = 10, standardize = TRUE, 
est_type="univariate")
hermite_est <- update_batch(hermite_est, rnorm(30))
quant_est <- quant(hermite_est, c(0.25, 0.5, 0.75))

hermiter documentation built on Nov. 17, 2021, 1:07 a.m.