median.hermite_estimator_univar

This generic method is a convenience wrapper around the quant method to 
calculate the median.

Facilitates estimation of full univariate and bivariate
probability density functions and cumulative distribution functions along with
full quantile functions (univariate) and nonparametric correlation
(bivariate) using Hermite series based estimators. These estimators are
particularly useful in the sequential setting (both stationary and
non-stationary) and one-pass batch estimation setting for large data sets.
Based on: Stephanou, Michael, Varughese, Melvin and Macdonald, Iain. "Sequential quantiles via Hermite series density estimation." Electronic Journal of Statistics 11.1 (2017): 570-607 <doi:10.1214/17-EJS1245>,
Stephanou, Michael and Varughese, Melvin. "On the properties of Hermite series based distribution function estimators." Metrika (2020) <doi:10.1007/s00184-020-00785-z> and Stephanou, Michael and Varughese, Melvin. "Sequential estimation of Spearman rank correlation using Hermite series estimators." Journal of Multivariate Analysis (2021) <doi:10.1016/j.jmva.2021.104783>.

Michael Stephanou

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)

Melvin Varughese

median.hermite_estimator_univar function

<dl><dt>x</dt>
<dd>A hermite_estimator_univar object.</dd>
<dt>...</dt>
<dd>Optional additional arguments to the quant function namely 
algorithm and accelerate_series.</dd></dl>

Arguments

Estimates the median — median.hermite_estimator_univar

<dl>

<dt>x</dt>
<dd>A hermite_estimator_univar object.</dd>


<dt>...</dt>
<dd>Optional additional arguments to the quant function namely 
algorithm and accelerate_series.</dd>

</dl>

median.hermite_estimator_univar: Estimates the median

Description

Usage

Value

Arguments