This repository contains the development version of fdaPDE package.
New features wrt CRAN: smooth regression for manifold and volumetric domains, also with areal data. Smooth fPCA over 2D, 2.5D and 3D domains, also with areal data. Smooth regression for space-time problems. Inference over linear and nonlinear components is also available for space and space-time models.
Compiled in Ubuntu using g++ compiler and in macOS: for the precise versions tested, see the report. If using a Linux machine, it is advisable to install rgl, geometry, plot3D and plot3Drgl before fdaPDE.
Image.FEM has been restored. Bugs in fPCA, boundary conditions and space-varying regression have been fixed. Issues of point location in 2.5D have been fixed. Compiled in Win RStudio, Ubuntu using g++ compiler and in macOS: for the precise versions tested, see the report. If using a Linux machine, it is advisable to install rgl, geometry, plot3D and before fdaPDE. If using Windows, it is advisable to install Rtools and then rgl, plot3D, geometry and RcppEigen libraries.
/src contains all C++ code and a special file named Makevars necessary to build and install the R package. The code is now organized in subfolders and divided into source files and header files. See the report for the precise new orgaization. We suggest to use a base-8 scale as spacing scale for visualization, in order to preserve the code style.
/R contains the R functions that wrap the C++ calls,
/data contains the data to run the tests in the examples,
/man contains the manual for the package.
Two different methods are proposed in order to install the package in the R environment.
.zip file from the repository, unzip it, and for the installation choose one of the two following methods:
install.packages("/path/to/fdaPDE", type='source', repos=NULL)
From the Terminal:
$ R CMD build <path to folder to be installed>
$ R CMD INSTALL -l <path name of the R library tree> <path to folder to be installed>
see the installation section in the report for more information.
1) the shift of indexes from R to C++ is done within the R functions smooth.FEM and FPCA.FEM Do not use C++ scripts directly on the R mesh objects, unless you take care of shifing indexes by yourself.
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