`R/aggregateSoilDepth.R`

`aggregateSoilDepth.Rd`

Estimate the most-likely depth to contact within a collection of soil profiles. Consider `getSoilDepthClass`

followed by group-wise percentile estimation as a faster alternative.

aggregateSoilDepth( x, groups, crit.prob = 0.9, name = hzdesgnname(x), p = "Cr|R|Cd", ... )

x | a |
---|---|

groups | the name of a site-level attribute that defines groups of profiles within a collection |

crit.prob | probability cutoff used to determine where the most likely depth to contact will be, e.g. 0.9 translates to 90% of profiles are shallower than this depth |

name | horizon-level attribute where horizon designation is stored, defaults to |

p | a REGEX pattern that matches non-soil genetic horizons |

... | additional arguments to |

A `data.frame`

is returned, with as many rows as there are unique group labels, as specified in `groups`

.

This function computes a probability-based estimate of soil depth by group. If no grouping variable exists, a dummy value can be used to compute a single estimate. The `crit.prob`

argument sets the critical probability (e.g. 0.9) at which soil depth within a group of profiles is determined. For example, a `crit.prob`

of 0.95 might result in an estimated soil depth (e.g. 120cm) where 95% of the profiles (by group) had depths that were less than or equal to 120cm.

D.E. Beaudette

data(sp1) depths(sp1) <- id ~ top + bottom site(sp1) <- ~ group # set horizon designation in SPC hzdesgnname(sp1) <- 'name' aggregateSoilDepth(sp1, 'group', crit.prob = 0.9) #> group soil.top soil.bottom #> 1 1 0 232 #> 2 2 0 67