WH.mat.prod

WH.mat.prod,MatH,MatH-method

WH.mat.prod,MatH-method

It is the matrix product of two <code>MatH</code> objects, i.e. two matrices of distributions,
by using the dot product of two histograms that is consistent with
 a set of distributions equipped with a L2 wasserstein metric.

In the framework of Symbolic Data Analysis, a relatively new
approach to the statistical analysis of multi-valued data, we consider
histogram-valued data, i.e., data described by univariate histograms. The
methods and the basic statistics for histogram-valued data are mainly based
on the L2 Wasserstein metric between distributions, i.e., the Euclidean metric
between quantile functions. The package contains unsupervised classification
techniques, least square regression and tools for histogram-valued data and for
histogram time series. An introducing paper is Irpino A. Verde R. (2015) <doi: 10.1007/s11634-014-0176-4>.

Antonio Irpino

HistDAWass

Histogram-Valued Data Analysis

WH.mat.prod function

<dl><dt>object1</dt>
<dd>a <code>MatH</code> object</dd>
<dt>object2</dt>
<dd>a <code>MatH</code> object</dd>
<dt>...</dt>
<dd>other optional parameters</dd>
<dt>traspose1</dt>
<dd>a logical value, default=FALSE. If TRUE trasposes object1</dd>
<dt>traspose2</dt>
<dd>a logical value, default=FALSE. If TRUE trasposes object2</dd></dl>

Arguments

Method WH.mat.prod — WH.mat.prod

<dl>

<dt>object1</dt>
<dd>a <code>MatH</code> object</dd>


<dt>object2</dt>
<dd>a <code>MatH</code> object</dd>


<dt>...</dt>
<dd>other optional parameters</dd>


<dt>traspose1</dt>
<dd>a logical value, default=FALSE. If TRUE trasposes object1</dd>


<dt>traspose2</dt>
<dd>a logical value, default=FALSE. If TRUE trasposes object2</dd>

</dl>

WH.mat.prod: Method WH.mat.prod

Description

Usage

Value

Arguments

Examples