Merge branch 'vegdist-na'

R/decostand.R

@@ -61,17 +61,26 @@
         x <- sweep(x, MARGIN, ran, "/")
         attr <- list("min" = tmp, "range" = ran, "margin" = MARGIN)
     }, rank = {
+        wasNA <- is.na(x)
+        if (any(wasNA) && !na.rm)
+            stop("missing values are not allowed with 'na.rm = FALSE'")
         if (missing(MARGIN)) MARGIN <- 1
         x[x==0] <- NA
         x <- apply(x, MARGIN, rank, na.last = "keep")
         if (MARGIN == 1) # gives transposed x
             x <- t(x)
         x[is.na(x)] <- 0
+        if(any(wasNA))
+            x[wasNA] <- NA
         attr <- list("margin" = MARGIN)
     }, rrank = {
         if (missing(MARGIN)) MARGIN <- 1
-        x <- decostand(x, "rank", MARGIN = MARGIN)
+        x <- decostand(x, "rank", MARGIN = MARGIN, na.rm = na.rm)
+        if (na.rm && any(wasNA <- is.na(x)))
+            x[wasNA] <- 0
         x <- sweep(x, MARGIN, specnumber(x, MARGIN = MARGIN), "/")
+        if (any(wasNA))
+            x[wasNA] <- NA
         attr <- list("margin" = MARGIN)
     }, standardize = {
         if (!missing(MARGIN) && MARGIN == 1)

R/veganMahatrans.R

@@ -7,10 +7,10 @@
 ### input must be correct: 'x' must be a centred matrix (not a
 ### data.frame, not raw data).
 `veganMahatrans` <-
-    function (x, s2, tol = sqrt(.Machine$double.eps))
+    function (x, s2, tol = sqrt(.Machine$double.eps), na.rm = FALSE)
 {
     if (missing(s2))
-        s2 <- cov(x)
+        s2 <- cov(x, use = if(na.rm) "pairwise.complete.obs" else "all.obs")
     e <- eigen(s2, symmetric = TRUE)
     k <- e$values > max(tol, tol * e$values[1L])
     sisqr <- e$vectors[,k, drop=FALSE] %*%

R/vegdist.R

@@ -35,16 +35,16 @@
         warning("results may be meaningless because data have negative entries
                  in method ",
                  dQuote(inm))
-    if (method %in% c(11,18) && any(colSums(x) == 0))
+    if (method %in% c(11,18) && any(colSums(x) == 0, na.rm = TRUE))
         warning("data have empty species which influence the results in
                  method ",
                 dQuote(inm))
     if (method == 6) # gower, but no altGower
         x <- decostand(x, "range", 2, na.rm = TRUE, ...)
     if (method == 16) # mahalanobis
-        x <- veganMahatrans(scale(x, scale = FALSE))
+        x <- veganMahatrans(scale(x, scale = FALSE), na.rm = na.rm)
     if (method == 18) # chisq
-        x <- decostand(x, "chi.square")
+        x <- decostand(x, "chi.square", na.rm = na.rm)
     if (method == 21)  # aitchison
         x <- decostand(x, "clr", ...)  # dots to pass possible pseudocount
     if (method == 22)  # robust.aitchison

man/decostand.Rd

@@ -26,7 +26,9 @@ decobackstand(x, zap = TRUE)
     subsets of data.  The dimensions of \code{MARGIN} must match with
     \code{x}. }
   \item{logbase}{The logarithm base used in \code{method = "log"}.}
-  \item{na.rm}{Ignore missing values in row or column standardizations.}
+  \item{na.rm}{Ignore missing values in row or column
+    standardizations. The \code{NA} values remain as \code{NA}, but they
+    are ignored in standardization of other values.}
   \item{zap}{Make near-zero values exact zeros to avoid negative
     values and exaggerated estimates of species richness.}
   \item{\dots}{Other arguments to the function (ignored).}

man/vegan-internal.Rd

@@ -35,7 +35,7 @@ getPermuteMatrix(perm, N, strata = NULL)
 howHead(x, ...)
 pasteCall(call, prefix = "Call:")
 veganCovEllipse(cov, center = c(0, 0), scale = 1, npoints = 100)
-veganMahatrans(x, s2, tol = sqrt(.Machine$double.eps))
+veganMahatrans(x, s2, tol = sqrt(.Machine$double.eps), na.rm = FALSE)
 hierParseFormula(formula, data)
 GowerDblcen(x, na.rm = TRUE)
 addLingoes(d)
@@ -95,7 +95,8 @@ addCailliez(d)
   distances are Mahalanobis distances. The input data \code{x} must be
   a matrix centred by columns, and \code{s2} its covariance matrix. If
   \code{s2} is not given, covariance matrix is found from \code{x}
-  within the function.
+  within the function. If \code{na.rm = TRUE}, \code{\link{cov}} is
+  called with \code{use = "pairwise.complete.obs"}.
 
   \code{hierParseFormula} returns a list of one matrix (left hand side)
   and a model frame with factors representing hierarchy levels 

man/vegdist.Rd

@@ -42,7 +42,8 @@
   \item{diag}{Compute diagonals. }
   \item{upper}{Return only the upper diagonal. }
   \item{na.rm}{Pairwise deletion of missing observations when
-    computing dissimilarities.}
+    computing dissimilarities (but some dissimilarities may still be
+    \code{NA}, although calculation is handled).}
   \item{\dots}{Other parameters.  These are ignored, except in
     \code{method ="gower"} which accepts \code{range.global} parameter of
     \code{\link{decostand}}, and in \code{method="aitchison"}, which