mfpcaPlot
(Package: Funclustering) :
Plot multivariate functional pca
This function plots the functional pca.
● Data Source:
CranContrib
● Keywords:
● Alias: mfpcaPlot
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mfpca
(Package: Funclustering) :
Multivariate functional pca
This function will run a weighted functional pca in the two cases of uni, and multivariate cases. If the observations (the curves) are given with weights, set up the parameter tik.
● Data Source:
CranContrib
● Keywords:
● Alias: mfpca
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This function plots the observed curves, before any action of smoothing or interpolation.
● Data Source:
CranContrib
● Keywords:
● Alias: plotOC
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cppMultiData
(Package: Funclustering) :
The C++ code, of this package take to run from the data two main information.
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. cppMultidata made this task in the multivariate case.
● Data Source:
CranContrib
● Keywords:
● Alias: cppMultiData
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cppUniData
(Package: Funclustering) :
The C++ code, of this package take to run from the data two main information.
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.
● Data Source:
CranContrib
● Keywords:
● Alias: cppUniData
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This class contains the input paramaters need to run the algorithm.
● Data Source:
CranContrib
● Keywords:
● Alias: Input-class
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This packages 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.
● Data Source:
CranContrib
● Keywords:
● Alias: Funclustering, Funclustering-package
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plotfd
(Package: Funclustering) :
plot a functional data object
This function plots a functional data object (after smoothing or interpolation). If you want to color the curves according to a cluster's membership, please specify the parmetere col. Note: this function works only for univariate functional data.
● Data Source:
CranContrib
● Keywords:
● Alias: plotfd
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This class contains the parameters in the output after running classification.
● Data Source:
CranContrib
● Keywords:
● Alias: Output-class
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harmsCut
(Package: Funclustering) :
Separates the matrices of the coefficients of harmonics
This function is used in mfpca to cut the harmonic coefficient matrix. In fact mfpca call a c++ mfpca which return (among others) the matrix of the coefficients of the harmonics in the basis expantion. But in the multivariate case the coefficient matrix for all dimension are store in the same matrix, so we use this function to store each dimension in the specific matrix.
● Data Source:
CranContrib
● Keywords:
● Alias: harmsCut
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providing 
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