Functions, data sets, analyses and examples from the 
  third edition of the book 
  ''A Handbook of Statistical Analyses Using R'' (Torsten Hothorn and Brian S.
  Everitt, Chapman & Hall/CRC, 2014). The first chapter
  of the book, which is entitled ''An Introduction to R'', 
  is completely included in this package, for all other chapters,
  a vignette containing all data analyses is available. In addition,
  Sweave source code for slides of selected chapters is included in 
  this package (see HSAUR3/inst/slides). The publishers web page is 
  '<http://www.crcpress.com/product/isbn/9781482204582>'.

The theoretical covariance between pairs of markers is calculated
    from either paternal haplotypes and maternal linkage disequilibrium (LD) or 
    vise versa. A genetic map is required. Grouping of markers is based on the 
    correlation matrix and a representative marker is suggested for each group.
    Employing the correlation matrix, optimal sample size can be derived for 
    association studies based on a SNP-BLUP approach.
    The implementation relies on paternal half-sib families and biallelic 
    markers. If maternal half-sib families are used, the roles of sire/dam are 
    swapped. Multiple families can be considered.
    Wittenburg, Bonk, Doschoris, Reyer (2020) "Design of Experiments for 
    Fine-Mapping Quantitative Trait Loci in Livestock Populations" 
    <doi:10.1186/s12863-020-00871-1>.
    Carlson, Eberle, Rieder, Yi, Kruglyak, Nickerson (2004) "Selecting a 
    maximally informative set of single-nucleotide polymorphisms for association
    analyses using linkage disequilibrium" <doi:10.1086/381000>.

We explore sparsity and homogeneity of regression coefficients incorporating prior constraint information. A general pairwise fusion approach is proposed to deal with the sparsity and homogeneity detection when combining prior convex constraints. We develop an modified alternating direction method of multipliers algorithm (ADMM) to obtain the estimators.