cv_mb: Cross-validation

In mbr: Mass Balance Reconstruction

Description

Cross-validation

Usage

cv_mb(
  instQ,
  pc.list,
  cv.folds,
  start.year,
  lambda = 1,
  log.trans = NULL,
  force.standardize = FALSE,
  return.type = c("fval", "metrics", "metric means", "Q")
)

Arguments

instQ	Instrumental data, in the same order as pc.list. The "season" column must be a factor.
pc.list	List of PC matrices
cv.folds	A list containing the cross validation folds
start.year	The first year of record
lambda	The penalty weight
log.trans	A vector containing indices of the targets to be log-transformed. If no transformation is needed, provide NULL.
force.standardize	If TRUE, all observations are standardized. See Details.
return.type	The type of results to be returned. Several types are possible to suit multiple use cases. fval Only the objective function value (penalized least squares) is returned; this is useful for the outer optimization for site selection. metrics all performance metrics are returned. metric means the Tukey's biweight robust mean of each metric is returned. Q The predicted flow in each cross-validation run is returned. This is the most basic output, so that you can use it to calculate other metrics that are not provided by the package.

Value

A data.table containing cross-validation results (metrics, fval, or metric means) for each target.

Examples

cvFolds <- make_Z(1922:2003, nRuns = 50, frac = 0.25, contiguous = TRUE)
cv <- cv_mb(p1Seasonal, pc3seasons, cvFolds, 1750, log.trans = 1:3, return.type = 'metrics')

mbr documentation built on Feb. 16, 2021, 5:07 p.m.