cppUniData

<p>The C++ code, of this package take to run from the data
  two main information. the coefficient in the basis
  expansion of the functional data, and the inner product
  between theses basis. cppUnidata made this task in the
  univariate case.</p>

This package proposes a model-based clustering algorithm for
multivariate functional data. The parametric mixture model, based on the
assumption of normality of the principal components resulting from a
multivariate functional PCA, is estimated by an EM-like algorithm. The main
advantage of the proposed algorithm is its ability to take into account the
dependence among curves.

ORPHANED

Funclustering

Functional Data Clustering

cppUniData function

The C++ code, of this package take to run from the data two main information.
the coefficient in the basis expansion of the functional data, and the inner product between theses basis.
cppUnidata made this task in the univariate case. — cppUniData

The C++ code, of this package take to run from the data two main information.
the coefficient in the basis expansion of the functional data, and the inner product between theses basis.
cppUnidata made this task in the univariate case.

cppUniData: The C++ code, of this package take to run from the data two main information. the coefficient in the basis expansion of the functional data, and the inner product between theses basis. cppUnidata made this task in the univariate case.

Description

Usage

Arguments

Value