Update log

Author: mingzehuang

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: latentcor
 Type: Package
 Title: Fast Computation of Latent Correlations for Mixed Data
-Version: 1.1.0
+Version: 1.2.0
 Authors@R: c(
     person(given = "Mingze",
            family = "Huang",

NEWS.md

@@ -4,3 +4,9 @@
 * Add help function `get_types` to automatically generate types for data matrix.
 * Add more documentation on parameters.
 * Add more documentation for speed comparison between original method and approximation.
+
+# latentcor 1.2.0
+
+* Add user-defined `use.nearPD`, so that user can decide if latent correlation matrix should be adjusted to be positive definite automatically.
+* Remove redundant code for checking positive definiteness.
+* Minor correction on types detection to accommodate `NA` values. 

R/latentcor.R

@@ -5,7 +5,7 @@
 #' @param X A numeric matrix or numeric data frame (n by p), where n is number of samples, and p is number of variables. Missing values (NA) are allowed, in which case the estimation is based on pairwise complete observations.
 #' @param types A vector of length p indicating the type of each of the p variables in \code{X}. Each element must be one of \code{"con"} (continuous), \code{"bin"} (binary), \code{"ter"} (ternary) or \code{"tru"} (truncated). If the vector has length 1, then all p variables are assumed to be of the same type that is supplied. The default value is \code{NULL}, and the variable types are determined automatically using function \code{\link{get_types}}. As automatic determination of variable types takes extra time, it is recommended to supply the types explicitly when they are known in advance.
 #' @param method The calculation method for latent correlations. Either \code{"original"} or \code{"approx"}. If \code{method = "approx"}, multilinear approximation method is used, which is much faster than the original method, see Yoon et al. (2021) for timing comparisons for various variable types. If \code{method = "original"}, optimization of the bridge inverse function is used. The default is \code{"approx"}.
-#' @param use.nearPD Logical indicator. \code{use.nearPD = TRUE} checks semi-positive definiteness of latent correlation matrix, get nearest positive definite matrix with shrinkage adjustment by \code{nu}. output \code{R} is the same as \code{Rpointwise} if \code{use.nearPD = FALSE}. Default value is TRUE.
+#' @param use.nearPD Logical indicator. \code{use.nearPD = TRUE} get nearest positive definite matrix with shrinkage adjustment by \code{nu}. Output \code{R} is the same as \code{Rpointwise} if \code{use.nearPD = FALSE}. Default value is TRUE.
 #' @param nu Shrinkage parameter for the correlation matrix, must be between 0 and 1. Guarantees that the minimal eigenvalue of returned correlation matrix is greater or equal to \code{nu}. When \code{nu = 0}, no shrinkage is performed, the returned correlation matrix will be semi-positive definite but not necessarily strictly positive definite. When \code{nu = 1}, the identity matrix is returned (not recommended).  The default (recommended) value is 0.001.
 #' @param tol When \code{method = "original"}, specifies the desired accuracy of the bridge function inversion via uniroot optimization and is passed to \code{\link{optimize}}. The default value is 1e-8. When \code{method = "approx"}, this parameter is ignored.
 #' @param ratio When \code{method = "approx"}, specifies the boundary value for multilinear interpolation, must be between 0 and 1. When \code{ratio = 0}, no linear interpolation is performed (the slowest execution) which is equivalent to \code{method = "original"}. When \code{ratio = 1}, linear interpolation is always performed (the fastest execution) but may lead to high approximation errors. The default (recommended) value is 0.9 which controls the approximation error and has fast execution, see Yoon et al. (2021) for details. When \code{method = "original"}, this parameter is ignored.