LaTeX

conversion

Author: erichson

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: rsvd
 Type: Package
 Title: Randomized Singular Value Decomposition
-Version: 1.0.1
+Version: 1.0.2
 Date: 2019-06-01
 Authors@R: c(person("N. Benjamin", "Erichson", role = c("aut", "cre"), email = "erichson@berkeley.edu"))
 Author: N. Benjamin Erichson [aut, cre]

R/rcur.R

@@ -40,6 +40,7 @@
 #'
 #'
 #' @return \code{rcur} returns a list with class \eqn{id} containing the following components:
+#'\describe{
 #'    \item{C}{ array_like; \cr
 #'              column subset \eqn{C = A[,C.idx]}; \eqn{(m, k)} dimensional array.
 #'    }
@@ -68,7 +69,7 @@
 #'    \item{R.scores}{ array_like; \cr
 #'                   scores  of the selected rows.
 #'    }                   
-#'                                                       
+#'}                                                       
 #'
 #' @references
 #' \itemize{
@@ -82,7 +83,8 @@
 #'          algorithms for constructing approximate matrix
 #'          decompositions" (2009).
 #'          (available at arXiv \url{http://arxiv.org/abs/0909.4061}).
-#' }
+#'}
+#'
 #'
 #' @author N. Benjamin Erichson, \email{erichson@berkeley.edu}
 #'

R/rid.R

@@ -50,6 +50,7 @@
 #'
 #'
 #' @return \code{rid} returns a list containing the following components:
+#' \describe{
 #'    \item{C}{ array_like; \cr
 #'              column subset \eqn{C = A[,idx]}, if \code{mode='column'}; array with dimensions \eqn{(m, k)}.
 #'    }
@@ -78,7 +79,7 @@
 #'    \item{scores.idx}{ array_like; \cr
 #'                  scores of the \eqn{k} selected columns or rows in \eqn{C} or \eqn{R}.                    
 #'    }
-#'
+#'}
 #'
 #' @references
 #' \itemize{
@@ -90,7 +91,8 @@
 #'   \item  [2] N. B. Erichson, S. Voronin, S. Brunton, J. N. Kutz.
 #'          "Randomized matrix decompositions using R" (2016).
 #'          (available at `arXiv \url{http://arxiv.org/abs/1608.02148}).
-#' }
+#'}
+#'
 #'
 #' @author N. Benjamin Erichson, \email{erichson@uw.edu}
 #'

R/rpca.R

@@ -50,6 +50,7 @@
 #'
 #'
 #' @return \code{rpca} returns a list with class \eqn{rpca} containing the following components:
+#' \describe{
 #'    \item{rotation}{  array_like; \cr
 #'                      the rotation (eigenvectors); \eqn{(n, k)} dimensional array.
 #'    }
@@ -66,6 +67,8 @@
 #'    \item{center, scale}{  array_like; \cr
 #'                     the centering and scaling used.
 #'    }
+#'}
+#'
 #'
 #' @note  The principal components are not unique and only defined up to sign
 #' (a constant of modulus one in the complex case) and so may differ between different
@@ -74,6 +77,7 @@
 #' Similar to \code{\link{prcomp}} the variances are computed with the usual divisor N - 1.
 #'
 #'
+#' @references
 #' \itemize{
 #'  \item [1] N. B. Erichson, S. Voronin, S. L. Brunton and J. N. Kutz. 2019.
 #'        Randomized Matrix Decompositions Using {R}. 
@@ -85,7 +89,8 @@
 #'          algorithms for constructing approximate matrix
 #'          decompositions" (2009).
 #'          (available at arXiv \url{http://arxiv.org/abs/0909.4061}).
-#' }
+#'}
+#'
 #'
 #' @author N. Benjamin Erichson, \email{erichson@berkeley.edu}
 #'

R/rqb.R

@@ -40,14 +40,18 @@
 #'
 #'
 #'@return \code{rqb} returns a list containing the following components:
+#' \describe{
 #'\item{Q}{  array_like; \cr
 #'           matrix with orthogonal columns; \eqn{(m, k)} dimensional array.
 #'}
 #'
 #'\item{B}{  array_like; \cr
 #'           smaller matrix; \eqn{(k, n)} dimensional array.
 #'}
+#'}
+#'
 #'
+#' @references
 #' \itemize{
 #'  \item [1] N. B. Erichson, S. Voronin, S. L. Brunton and J. N. Kutz. 2019.
 #'        Randomized Matrix Decompositions Using {R}. 
@@ -59,7 +63,7 @@
 #'          algorithms for constructing approximate matrix
 #'          decompositions" (2009).
 #'          (available at arXiv \url{http://arxiv.org/abs/0909.4061}).
-#' }
+#'}
 #'
 #' @author N. Benjamin Erichson, \email{erichson@berkeley.edu}
 #' 

R/rrpca.R

@@ -40,18 +40,19 @@
 #'
 #'
 #' @return \code{rrpca} returns a list containing the following components:
+#' \describe{
 #'    \item{L}{  array_like; \cr
 #'              low-rank component; \eqn{(m, n)} dimensional array.
 #'    }
 #'    \item{S}{  array_like \cr
 #'               sparse component; \eqn{(m, n)} dimensional array.
 #'    }
-#'
+#'}
 #'
 #' @author N. Benjamin Erichson, \email{erichson@berkeley.edu}
 #'
 #'
-#'
+#' @references
 #' \itemize{
 #'  \item [1] N. B. Erichson, S. Voronin, S. L. Brunton and J. N. Kutz. 2019.
 #'        Randomized Matrix Decompositions Using {R}. 
@@ -64,7 +65,6 @@
 #'          (available at arXiv \url{http://arxiv.org/abs/1009.5055}).
 #' }
 #'
-#'
 #' @examples
 #' library('rsvd')
 #'

R/rsvd.R

@@ -53,6 +53,7 @@
 #'                		\eqn{'rademacher'} : Rademacher random variates. \cr
 #'
 #'@return \code{rsvd} returns a list containing the following three components:
+#'\describe{
 #'\item{d}{  array_like; \cr
 #'           singular values; vector of length \eqn{(k)}.
 #'}
@@ -64,6 +65,7 @@
 #'\item{v}{  array_like; \cr
 #'           right singular vectors; \eqn{(n, k)} or \eqn{(n, nv)} dimensional array. \cr
 #'}
+#'}
 #'
 #' @note The singular vectors are not unique and only defined up to sign
 #' (a constant of modulus one in the complex case). If a left singular vector
@@ -78,7 +80,7 @@
 #'        Journal of Statistical Software, 89(11), 1-48.
 #'        \url{http://doi.org/10.18637/jss.v089.i11}.
 #' 
-#'   \item  [2] N. Halko, P. Martinsson, and J. Tropp.
+#'  \item  [2] N. Halko, P. Martinsson, and J. Tropp.
 #'          "Finding structure with randomness: probabilistic
 #'          algorithms for constructing approximate matrix
 #'          decompositions" (2009).

README.md

@@ -71,6 +71,11 @@ devtools::install_github("erichson/rsvd")
 
 The source packge can be obtained here: [CRAN: rsvd](https://cran.r-project.org/web/packages/rsvd/index.html).
 
+## New in Version 1.0.2
+
+* Several small issues are fixed.
+* Thanks to Aaron Lun, who has fixed a bug in the rsvd function that occured when nu=0 or nv=0.
+
 ## New in Version 1.0.0
 
 * Support for non-default matrix types to deal with large-scale matrices that are held on file, added by Aaron Lun.
@@ -86,7 +91,6 @@ The source packge can be obtained here: [CRAN: rsvd](https://cran.r-project.org/
 ## Cite as
 
 ```
-
 @Article{,
     title = {Randomized Matrix Decompositions Using {R}},
     author = {N. Benjamin Erichson and Sergey Voronin and Steven L.
@@ -98,7 +102,6 @@ The source packge can be obtained here: [CRAN: rsvd](https://cran.r-project.org/
     pages = {1--48},
     doi = {10.18637/jss.v089.i11},
 }
-
 ```