Added code

.Rbuildignore

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+^.*\.Rproj$
+^\.Rproj\.user$
+Notes.txt

.gitignore

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+.Rproj.user
+.Rhistory
+.RData
+.Ruserdata
+src/*.o
+src/*.so
+src/*.dll
+Notes.txt
+

AlphaMME.Rproj

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+Version: 1.0
+
+RestoreWorkspace: Default
+SaveWorkspace: Default
+AlwaysSaveHistory: Default
+
+EnableCodeIndexing: Yes
+UseSpacesForTab: Yes
+NumSpacesForTab: 2
+Encoding: UTF-8
+
+RnwWeave: Sweave
+LaTeX: pdfLaTeX
+
+AutoAppendNewline: Yes
+StripTrailingWhitespace: Yes
+
+BuildType: Package
+PackageUseDevtools: Yes
+PackageInstallArgs: --no-multiarch --with-keep.source
+PackageRoxygenize: rd,collate,namespace

DESCRIPTION

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+Package: AlphaMME
+Type: Package
+Title: Alpha Mixed Model Equations
+Version: 0.1.0
+Date: 2018-01-25
+Authors@R: c(person("Chris","Gaynor",email="[email protected]",role="cre"))
+Description: This package contains mixed model equation solvers written in C++.
+License: MIT + file LICENSE
+URL: https://bitbucket.org/hickeyjohnteam/alphamme
+Imports: Rcpp (>= 0.12.13), RcppArmadillo
+LinkingTo: Rcpp, RcppArmadillo
+RoxygenNote: 6.0.1
+NeedsCompilation: true

NAMESPACE

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+# Generated by roxygen2: do not edit by hand
+
+export(calcD)
+export(calcG)
+export(calcGIbs)
+export(fastDist)
+export(fastPairDist)
+export(gaussKernel)
+export(readMat)
+export(solveAniModel)
+export(solveMKM)
+export(solveMVM)
+export(solveRRBLUP)
+export(solveRRBLUPMK)
+export(solveRRBLUPMV)
+export(solveUVM)
+import(Rcpp)
+import(RcppArmadillo)
+useDynLib(AlphaMME, .registration = TRUE)

R/AlphaMME.R

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+#' @useDynLib AlphaMME, .registration = TRUE
+#' @import Rcpp RcppArmadillo
+
+#' @title Alpha Mixed Model Equations
+#'
+#' @description
+#' This package contains mixed model equation solvers written in C++.
+#'
+#' @docType package
+#' @name AlphaMME-package
+NULL

R/RcppExports.R

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+# Generated by using Rcpp::compileAttributes() -> do not edit by hand
+# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
+
+#' @title Read Matrix
+#'
+#' @description
+#' Uses C++ to quickly read a matrix from a text
+#' file. Requires knowledge of the number of rows
+#' and columns in the file.
+#'
+#' @param fileName path to the file to read
+#' @param rows number of rows to read in
+#' @param cols number of columns to read in
+#' @param sep a single character seperating data entries
+#' @param skipRows number of rows to skip
+#' @param skipCols number of columns to skip
+#'
+#' @return a numeric matrix
+#'
+#' @export
+readMat <- function(fileName, rows, cols, sep = ' ', skipRows = 0L, skipCols = 0L) {
+    .Call(`_AlphaMME_readMat`, fileName, rows, cols, sep, skipRows, skipCols)
+}
+
+#' @title Solve Univariate Model
+#'
+#' @description
+#' Solves a univariate mixed model of form \eqn{y=X\beta+Zu+e}
+#'
+#' @param y a matrix with n rows and 1 column
+#' @param X a matrix with n rows and x columns
+#' @param Z a matrix with n rows and m columns
+#' @param K a matrix with m rows and m columns
+#'
+#' @export
+solveUVM <- function(y, X, Z, K) {
+    .Call(`_AlphaMME_solveUVM`, y, X, Z, K)
+}
+
+#' @title Solve animal model
+#'
+#' @description
+#' Solves a univariate mixed model of form \eqn{y=X\beta+u+e}
+#'
+#' @param y a matrix with n rows and 1 column
+#' @param X a matrix with n rows and x columns
+#' @param K the numeric relationship matrix 
+#' with n rows and n columns
+#'
+#' @export
+solveAniModel <- function(y, X, K) {
+    .Call(`_AlphaMME_solveAniModel`, y, X, K)
+}
+
+#' @title Solve RR-BLUP
+#'
+#' @description
+#' Solves a univariate mixed model of form \eqn{y=X\beta+Mu+e}
+#'
+#' @param y a matrix with n rows and 1 column
+#' @param X a matrix with n rows and x columns
+#' @param M a matrix with n rows and m columns
+#'
+#' @export
+solveRRBLUP <- function(y, X, M) {
+    .Call(`_AlphaMME_solveRRBLUP`, y, X, M)
+}
+
+#' @title Solve Multivariate Model
+#'
+#' @description
+#' Solves a multivariate mixed model of form \eqn{Y=X\beta+Zu+e}
+#'
+#' @param Y a matrix with n rows and q columns
+#' @param X a matrix with n rows and x columns
+#' @param Z a matrix with n rows and m columns
+#' @param K a matrix with m rows and m columns
+#' @param tol tolerance for convergence
+#' @param maxIter maximum number of iteration
+#'
+#' @export
+solveMVM <- function(Y, X, Z, K, tol = 1e-6, maxIter = 1000L) {
+    .Call(`_AlphaMME_solveMVM`, Y, X, Z, K, tol, maxIter)
+}
+
+#' @title Solve Multivariate RR-BLUP
+#'
+#' @description
+#' Solves a multivariate mixed model of form \eqn{Y=X\beta+Mu+e}
+#'
+#' @param Y a matrix with n rows and q columns
+#' @param X a matrix with n rows and x columns
+#' @param M a matrix with n rows and m columns
+#' @param tol tolerance for convergence
+#' @param maxIter maximum number of iteration
+#'
+#' @export
+solveRRBLUPMV <- function(Y, X, M, tol = 1e-6, maxIter = 1000L) {
+    .Call(`_AlphaMME_solveRRBLUPMV`, Y, X, M, tol, maxIter)
+}
+
+#' @title Solve Multikernel Model
+#'
+#' @description
+#' Solves a univariate mixed model with multiple random effects.
+#'
+#' @param y a matrix with n rows and 1 column
+#' @param X a matrix with n rows and x columns
+#' @param Zlist a list of Z matrices
+#' @param Klist a list of K matrices
+#' @param maxIter maximum number of iteration
+#'
+#' @export
+solveMKM <- function(y, X, Zlist, Klist, maxIter = 40L) {
+    .Call(`_AlphaMME_solveMKM`, y, X, Zlist, Klist, maxIter)
+}
+
+#' @title Solve Multikernel RR-BLUP
+#'
+#' @description
+#' Solves a univariate mixed model with multiple random effects.
+#'
+#' @param y a matrix with n rows and 1 column
+#' @param X a matrix with n rows and x columns
+#' @param Mlist a list of M matrices
+#' @param maxIter maximum number of iteration
+#'
+#' @export
+solveRRBLUPMK <- function(y, X, Mlist, maxIter = 40L) {
+    .Call(`_AlphaMME_solveRRBLUPMK`, y, X, Mlist, maxIter)
+}
+
+#' @title Calculate G Matrix
+#'
+#' @description
+#' Calculates the genomic relationship matrix.
+#'
+#' @param X a matrix of marker genotypes scored as 0,1,2
+#'
+#' @return a matrix of the realized genomic relationships
+#'
+#' @export
+calcG <- function(X) {
+    .Call(`_AlphaMME_calcG`, X)
+}
+
+#' @title Calculate Dominance Matrix
+#'
+#' @description
+#' Calculates the dominance relationship matrix.
+#'
+#' @param X a matrix of marker genotypes scored as 0,1,2
+#'
+#' @references
+#' \cite{Nishio, M, and M. Satoh. 2014. Including Dominance Effects in the Genomic BLUP Method for Genomic Evaluation. PLOS ONE 9(1): e85792.}
+#' 
+#' @return a matrix of the realized dominance relationships
+#'
+#' @export
+calcD <- function(X) {
+    .Call(`_AlphaMME_calcD`, X)
+}
+
+#' @title Calculate IBS G Matrix
+#'
+#' @description
+#' Calculates an identity-by-state genomic relationship matrix
+#' based on simple matching.
+#'
+#' @param X a matrix of marker genotypes scored as 0,1,2
+#'
+#' @return a matrix of genomic relationships
+#'
+#' @export
+calcGIbs <- function(X) {
+    .Call(`_AlphaMME_calcGIbs`, X)
+}
+
+#' @title Calculate Euclidean distance
+#'
+#' @description
+#' Calculates a Euclidean distance matrix using a binomial
+#' theorem trick. Results in much faster computation than the
+#' \code{dist} function in package \code{stats}.
+#'
+#' @param X a numeric matrix
+#'
+#' @return a matrix of columnwise distances
+#'
+#' @export
+fastDist <- function(X) {
+    .Call(`_AlphaMME_fastDist`, X)
+}
+
+#' @title Calculate Paired Euclidean distance
+#'
+#' @description
+#' Calculates a Euclidean distance between two matrices using
+#' a binomial theorem trick.
+#'
+#' @param X a numeric matrix
+#' @param Y a numeric matrix
+#'
+#' @return a matrix of columnwise distances between matrices
+#' X and Y
+#'
+#' @export
+fastPairDist <- function(X, Y) {
+    .Call(`_AlphaMME_fastPairDist`, X, Y)
+}
+
+#' @title Calculate Gaussian Kernel
+#'
+#' @description
+#' Calculates a Gaussian kernel using a Euclidean distance
+#' matrix.
+#'
+#' @param D a matrix of Euclidean distances,
+#' see \code{\link{fastDist}}
+#' @param theta the tuning parameter
+#'
+#' @return a numeric matrix
+#'
+#' @export
+gaussKernel <- function(D, theta) {
+    .Call(`_AlphaMME_gaussKernel`, D, theta)
+}
+