Data-driven evaluation of generalized horizon labels using nMDS and silhouette width.

evalGenHZ(
  obj,
  genhz = GHL(obj, required = TRUE),
  vars,
  non.matching.code = "not-used",
  stand = TRUE,
  trace = FALSE,
  metric = "euclidean"
)

Arguments

obj

a SoilProfileCollection object

genhz

name of horizon-level attribute containing generalized horizon labels

vars

character vector of horizon-level attributes to include in the evaluation

non.matching.code

code used to represent horizons not assigned a generalized horizon label

stand

standardize variables before computing distance matrix (default = TRUE), passed to daisy

trace

verbose output from passed to isoMDS, (default = FALSE)

metric

distance metric, passed to daisy

Value

a list is returned containing:

horizons

c('mds.1', 'mds.2', 'sil.width', 'neighbor')

stats

mean and standard deviation of vars, computed by generalized horizon label

dist

the distance matrix as passed to isoMDS

Details

Non-metric multidimensional scaling is performed via isoMDS. The input distance matrix is generated by 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 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.

See also

Author

D.E. Beaudette