diff --git a/news/index.html b/news/index.html index 9bceeee0..4b166185 100644 --- a/news/index.html +++ b/news/index.html @@ -76,7 +76,7 @@
plotSPC()
now adjusted as function of number of profiles and device widthplotSPC()
saved to last_spc_plot
in aqp.env
diff --git a/pkgdown.yml b/pkgdown.yml
index 18f1f70c..d0d217ba 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -9,4 +9,4 @@ articles:
Munsell-color-conversion: Munsell-color-conversion.html
NCSP: NCSP.html
new-in-aqp-2: new-in-aqp-2.html
-last_built: 2024-07-25T18:21Z
+last_built: 2024-07-30T20:56Z
diff --git a/reference/evalGenHZ.html b/reference/evalGenHZ.html
index 635ef361..e7d80989 100644
--- a/reference/evalGenHZ.html
+++ b/reference/evalGenHZ.html
@@ -103,62 +103,50 @@ name of horizon-level attribute containing generalized horizon -labels
name of horizon-level attribute containing generalized horizon labels
character vector of horizon-level attributes to include in the -evaluation
character vector of horizon-level attributes to include in the evaluation
code used to represent horizons not assigned a -generalized horizon label
code used to represent horizons not assigned a generalized horizon label
standardize variables before computing distance matrix (default
-= TRUE), passed to daisy
standardize variables before computing distance matrix, passed to cluster::daisy()
verbose output from passed to isoMDS
, (default =
-FALSE)
verbose output from passed to MASS::isoMDS()
distance metric, passed to daisy
distance metric, passed to cluster::daisy()
a list is returned containing:
c('mds.1', -'mds.2', 'sil.width', 'neighbor')
mean and standard deviation
-of vars
, computed by generalized horizon label
the
-distance matrix as passed to isoMDS
a list is returned containing:
horizons: c('mds.1', mds.2', 'sil.width', 'neighbor')
stats: mean and standard deviation vars
, computed by generalized horizon label
dist: the distance matrix as passed to MASS::isoMDS()
Non-metric multidimensional scaling is performed via isoMDS
.
-The input distance matrix is generated by daisy
using
+
Non-metric multidimensional scaling is performed via MASS::isoMDS()
.
+The input distance matrix is generated by cluster::daisy()
using
(complete cases of) horizon-level attributes from obj
as named in
vars
.
Silhouette widths are computed via silhouette
. The input
-distance matrix is generated by daisy
using (complete cases
+
Silhouette widths are computed via cluster::silhouette()
. The input
+distance matrix is generated by cluster::daisy()
using (complete cases
of) horizon-level attributes from obj
as named in vars
. Note
that observations with genhz labels specified in non.matching.code
are removed filtered before calculation of the distance matrix.