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Installation

Being a header-only library, lesstimate is fairly easy to install. However, depending on your use-case, the dependencies of lesstimate have to be installed differently.

Using lesstimate in your R package

We provide a package template using lesstimate. All procedures outlined in the following are already implemented in this template.

When using lesstimate in your R package, first make sure that RcppArmadillo (Eddelbuettel et al., 2014) is installed (if not, run install.packages("RcppArmadillo"). You will also need a C++ compiler. Instructions to install C++ can be found in the Advanced R book by Hadley Wickham.

Next, create a folder called inst in your R package. Within inst, create a folder called include. You should now have the following folder structure:

|- R
|- inst
|    |- include
|- src
|    |- Makevars
|    |- Makevars.win
|- DESCRIPTION
|- .Rbuildignore

Clone the lesstimate git repository in your include folder with git clone https://github.com/jhorzek/lesstimate.git.

Add a file called lessSEM.h in the folder inst/include (see here for an example) and save the following in this file:

#ifndef lessSEM_H
#define lessSEM_H

#include "lesstimate/include/lesstimate.h"

#endif

This file makes sure that R can find the functions of lesstimate.

In your src-folder, open the files Makevars and Makevars.win. Add the following line (see here): 

PKG_CXXFLAGS = $(SHLIB_OPENMP_CXXFLAGS) -I../inst/include/
This ensures that the include folder is found when compiling the package.

Next add ^lesstimateConfig-cmake$ to .Rbuildignore.

Open the DESCRIPTION file of your package and add Rcpp and RcppArmadillo to the field LinkingTo (see here).

Using lesstimate in your C++ package

We provide a template using lesstimate with C++. All procedures outlined in the following are already implemented in this template. We highly recommend that you use this template as a starting point.

For C++, you will need the armadillo - library (Sanderson et al., 2016). lesstimate uses the cpm.Cmake package manager to handle its dependencies. However, not all dependencies will be installed automatically. armadillo requires BLAS and LAPACK, both of which have to be installed on the system. Instructions to install dependencies of armadillo are provided in the documentation of the package.

References

  • Eddelbuettel D, Sanderson C (2014). “RcppArmadillo: Accelerating R with high-performance C++ linear algebra.” Computational Statistics and Data Analysis, 71, 1054–1063. doi:10.1016/j.csda.2013.02.005.
  • Sanderson C, Curtin R (2016). Armadillo: a template-based C++ library for linear algebra. Journal of Open Source Software, 1 (2), pp. 26.