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fdaPDE (version 0.1-1)

Regression with Partial Differential Regularizations, using the Finite Element Method

Description

An implementation of regression models with partial differential regularizations, making use of the Finite Element Method. The models efficiently handle data distributed over irregularly shaped domains and can comply with various conditions at the boundaries of the domain. A priori information about the spatial structure of the phenomenon under study can be incorporated in the model via the differential regularization.

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Version

Install

install.packages('fdaPDE')

Monthly Downloads

245

Version

0.1-1

License

CC BY-NC-SA 4.0

Maintainer

Eardi Lila

Last Published

January 15th, 2016

Functions in fdaPDE (0.1-1)

R_eval.FEM.basis

Evaluate Finite Element bases and their Derivatives at a set of locations
MeuseData

Meuse river data set
R_eval.FEM

Evaluate a FEM object at a set of locations
create.MESH.2D

Create a triangular mesh
R_elementProperties

Compute some properties for each triangular element of the mesh
plot.MESH2D

Plot a MESH2D object
refine.MESH.2D

Refine a triangular mesh
MeuseBorder

Boundary of the Meuse River data set
R_stiff

Compute the stiffness matrix
eval.FEM

Evaluate a FEM object at a set of point locations
create.FEM.basis

Create a FEM basis
mesh.2D.rectangular

Simple Rectangular mesh
image.FEM

Image Plot of a FEM object
R_mass

Compute the mass matrix
smooth.FEM.PDE.sv.basis

Spatial regression with differential regularization: anysotropic and non-stationary case (elliptic PDE with space-varying coefficients)
mesh.2D.simple

Simple mesh
smooth.FEM.PDE.basis

Spatial regression with differential regularization: anysotropic case (elliptic PDE)
plot.FEM

Plot a FEM object
R_smooth.FEM.basis

Spatial regression with differential regularization (fully implemented in R code)
FEM

Define a surface or spatial field by a Finite Element basis expansion
smooth.FEM.basis

Spatial regression with differential regularization: stationary and isotropic case (Laplacian)