Create Representative Soil Profiles via L1 Estimator

Source: R/L1_profiles.R

The L1 estimator, or geometric median, is a multivariate generalization of the (univariate) median concept. This function performs a multivariate aggregation (via L1 estimator) according to a suite of ratio-scale soil properties. The L1 estimator is applied to soil profile data that have been sliced to a 1-depth-unit basis. Data should be well stratified by groups defined in fm, otherwise the L1 median may not make any sense.

See the L1 Profiles Tutorial for additional examples.

L1_profiles(
  x,
  fm,
  basis = 1,
  method = c("regex", "simple", "constant"),
  maxDepthRule = c("max", "min"),
  maxDepthConstant = NULL
)

Arguments

x

SoilProfileCollection object

fm

formula, for example: group ~ p1 + p2 + p3, where "group" is a site-level grouping variable, and "p1", "p2", and "p3" are horizon level variables

basis

positive integer, aggregation basis (e.g. 1 for 1-depth-unit intervals). Values other than 1 are not currently supported.

method

soil depth evaluation method: "regex" for regular expression, "simple", or "constant". See details.

maxDepthRule

maximum depth rule: "max" or "min" See details.

maxDepthConstant

positive integer, maximum depth when maxDepthRule = 'constant'

Value

a SoilProfileCollection object

Details

See this related tutorial for additional examples. The method, maxDepthRule, and maxDepthConstant arguments set the maximum depth (over the entire collection) of analysis used to build "L1 profiles". The following rules are available:

  • method = 'regex' uses pattern matching on horizon designations (note that hzdesgnname metadata must be set with hzdesgnname(x) <- 'columnname')

  • method = 'simple' uses min or max as applied to x, no accounting for non-soil horizons (e.g. Cr or R)

  • method = 'constant' uses a fixed depth value supplied by maxDepthConstant

The maxDepthRule argument sets depth calculation constraint, applied to soil depths computed according to method (min or max).

Note

This function requires the Gmedian package.

References

Cardot, H., Cenac, P. and Zitt, P-A. (2013). Efficient and fast estimation of the geometric median in Hilbert spaces with an averaged stochastic gradient algorithm. Bernoulli, 19, 18-43.