update_sequential: Updates the Hermite series based estimator sequentially

In hermiter: Efficient Sequential and Batch Estimation of Univariate and Bivariate Probability Density Functions and Cumulative Distribution Functions along with Quantiles (Univariate) and Nonparametric Correlation (Bivariate)

Updates the Hermite series based estimator sequentially

Description

This method can be applied in sequential estimation settings.

Usage

update_sequential(h_est_obj, x)

Arguments

h_est_obj	A hermite_estimator_univar or hermite_estimator_bivar object.
x	A numeric vector or matrix. Observations to be incorporated into the estimator. Note that for univariate estimators, x is a numeric vector whereas for bivariate estimators, x is a numeric vector of length 2 or a n x 2 matrix with n bivariate observations to be incorporated into the estimator.

Value

An object of class hermite_estimator_univar or hermite_estimator_bivar.

Examples

## Not run: 
hermite_est <- hermite_estimator(N = 10, standardize = TRUE, 
est_type="univariate")
hermite_est <- update_sequential(hermite_est, x = 2)
hermite_est <- hermite_estimator(N = 10, standardize = TRUE, 
est_type="bivariate")
hermite_est <- update_sequential(hermite_est, x = c(1,2))

## End(Not run)

hermiter documentation built on May 31, 2023, 6:30 p.m.