Version 0.2.1.1. Replaced deprecated Matrix package functions cBind a…

…nd rBind with their cbind and rbind counterparts.

DESCRIPTION

@@ -2,8 +2,8 @@ Package: sparseMVN
 Type: Package
 Title: Multivariate Normal Functions for Sparse Covariance and Precision
     Matrices
-Version: 0.2.1
-Date: 2017-05-23
+Version: 0.2.1.1
+Date: 2018-03-26
 Authors@R: person(given="Michael", family="Braun", email="[email protected]", role=c("aut","cre","cph"))
 Maintainer: Michael Braun <[email protected]>
 URL: http://www.smu.edu/Cox/Departments/FacultyDirectory/BraunMichael
@@ -12,9 +12,9 @@ Description: Computes multivariate normal (MVN) densities, and
     precision matrix is sparse.
 License: MPL (>= 2.0)
 Depends:
-    R (>= 3.4.0)
+    R (>= 3.4.4)
 Imports:
-    Matrix (>= 1.2.8),
+    Matrix (>= 1.2.12),
     methods
 Suggests:
     mvtnorm (>= 1.0.6),

NEWS

@@ -2,6 +2,9 @@
 
 NEWS FILE FOR SPARSEMVN PACKAGE
 
+VERSION 0.2.1.1 (Mar. 26, 2018)
+
+-   Removed deprecated Matrix package functions cBind and rBind.
 
 VERSION 0.2.1
 

NEWS.md

@@ -1,5 +1,10 @@
 # NEWS file for sparseMVN package
 
+## VERSION 0.2.1.1 (Mar. 26, 2018)
+
+*  Removed deprecated Matrix package functions cBind and rBind.
+
+
 ## VERSION 0.2.1 (May 23, 2017)
 
 * New vignette.

R/binary.R

@@ -90,7 +90,7 @@ binary.hess <- function(P, data, priors, order.row=FALSE) {
     }
 
     Bmu <- .d2.dmu(N,SX, XO)
-    res <- rbind(cbind(B2, Matrix::t(cross)),cBind(cross, Bmu))
+    res <- rbind(cbind(B2, Matrix::t(cross)),cbind(cross, Bmu))
 
     return(drop0(res))
 }

R/rmvn-sparse.R

@@ -35,8 +35,8 @@
 #' 
 #' ## build sample sparse covariance matrix
 #'    Q1 <- tril(kronecker(Matrix(seq(0.1,p,length=p*p),p,p),diag(m)))
-#'    Q2 <- cBind(Q1,Matrix(0,m*p,k))
-#'    Q3 <- rBind(Q2,cBind(Matrix(rnorm(k*m*p),k,m*p),Diagonal(k)))
+#'    Q2 <- cbind(Q1,Matrix(0,m*p,k))
+#'    Q3 <- rbind(Q2,cbind(Matrix(rnorm(k*m*p),k,m*p),Diagonal(k)))
 #'    V <- tcrossprod(Q3)
 #'    CH <- Cholesky(V)
 #' 

tests/testthat/test_sparseMVN.R

@@ -14,8 +14,8 @@ test_that("sparseMVN", {
 
     mu <- seq(-3,3,length=p*m+k)
     Q1 <- tril(kronecker(Matrix(seq(0.1,p,length=p*p),p,p),diag(m)))
-    Q2 <- cBind(Q1,Matrix(0,m*p,k))
-    Q3 <- rBind(Q2,cBind(Matrix(rnorm(k*m*p),k,m*p),Diagonal(k)))
+    Q2 <- cbind(Q1,Matrix(0,m*p,k))
+    Q3 <- rbind(Q2,cbind(Matrix(rnorm(k*m*p),k,m*p),Diagonal(k)))
     CV <- Matrix::tcrossprod(Q3)
     chol.CV <- Matrix::Cholesky(CV)  ## creates a dCHMsimpl object
 

vignettes/replication.R

@@ -15,8 +15,8 @@ registerDoParallel(cores=cores)
 build_mat <- function(N, k) {
     t1 <- exp(rnorm(k*k))
     Q1 <- tril(kronecker(diag(N),Matrix(t1,k,k)))
-    Q2 <- cBind(Q1,Matrix(0, N*k, k))
-    Q3 <- rBind(Q2,cBind(Matrix(rnorm(N*k*k), k, N*k), Diagonal(k)))
+    Q2 <- cbind(Q1,Matrix(0, N*k, k))
+    Q3 <- rbind(Q2,cbind(Matrix(rnorm(N*k*k), k, N*k), Diagonal(k)))
     tcrossprod(Q3)
 }
 

vignettes/sparseMVN.Rnw

@@ -354,17 +354,17 @@ Now the Hessian has an "banded" sparsity pattern, as in Figure~\ref{fig:banded}.
    \begin{subfigure}[b]{.5\textwidth}
 <<blockarrow, echo=FALSE, comment=NA>>=
 Mat <- as(kronecker(diag(N), matrix(1, k, k)),"sparseMatrix")
-Mat <- rBind(Mat, Matrix(1, p, N*k))
-Mat <- cBind(Mat, Matrix(1, k*N+p, p))
+Mat <- rbind(Mat, Matrix(1, p, N*k))
+Mat <- cbind(Mat, Matrix(1, k*N+p, p))
 printSpMatrix(as(Mat,"nMatrix"))
 @
 \caption{A ``block-arrow'' sparsity pattern.}\label{fig:blockarrow}
 \end{subfigure}%
 \begin{subfigure}[b]{.5\textwidth}
 <<banded, echo=FALSE, comment=NA>>=
 Mat <- kronecker(Matrix(1, k, k), diag(N))
-Mat <- rBind(Mat, Matrix(1, p, N * k))
-Mat <- cBind(Mat, Matrix(1, k*N+p, p))
+Mat <- rbind(Mat, Matrix(1, p, N * k))
+Mat <- cbind(Mat, Matrix(1, k*N+p, p))
 printSpMatrix(as(Mat,"nMatrix"))
 @
  \caption{A ``banded'' sparsity pattern.}\label{fig:banded}
@@ -375,8 +375,8 @@ printSpMatrix(as(Mat,"nMatrix"))
 
 <<echo=FALSE, results="hide">>=
 Mat2 <- as(kronecker(diag(Q),matrix(1,k,k)),"lMatrix") %>%
-    rBind(Matrix(TRUE,p,Q*k)) %>%
-    cBind(Matrix(TRUE, k*Q+p, p)) %>%
+    rbind(Matrix(TRUE,p,Q*k)) %>%
+    cbind(Matrix(TRUE, k*Q+p, p)) %>%
     as("dgCMatrix") %>%
     as("symmetricMatrix")
 A2 <- as(Mat2,"matrix")