dens.hermite_estimator_bivar

This method calculates the probability density values for a matrix of 
2-d x vector values using the hermite_estimator_bivar object (h_est_obj).

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

dens.hermite_estimator_bivar function

<dl><dt>h_est_obj</dt>
<dd>A hermite_estimator_bivar object.</dd>
<dt>x</dt>
<dd>A numeric matrix. Each row corresponds to a 2-d coordinate.</dd>
<dt>clipped</dt>
<dd>A boolean value. This value determines whether
probability densities are clipped to be bigger than zero.</dd>
<dt>accelerate_series</dt>
<dd>A boolean value. Series acceleration has not yet 
been implemented for bivariate estimators.</dd></dl>

Arguments

Estimates the probability densities for a matrix of 2-d x values — dens.hermite_estimator_bivar

<dl>

<dt>h_est_obj</dt>
<dd>A hermite_estimator_bivar object.</dd>


<dt>x</dt>
<dd>A numeric matrix. Each row corresponds to a 2-d coordinate.</dd>


<dt>clipped</dt>
<dd>A boolean value. This value determines whether
probability densities are clipped to be bigger than zero.</dd>


<dt>accelerate_series</dt>
<dd>A boolean value. Series acceleration has not yet 
been implemented for bivariate estimators.</dd>

</dl>

dens.hermite_estimator_bivar: Estimates the probability densities for a matrix of 2-d x values

Description

Usage

Value

Arguments

Details