deshrink: Deshrinking techniques for WA transfer functions

Description

In Weighted Averaging models averages are taken twice and thus WA estimates shrink towards the training set mean and need to be deshrunk.deshrink performs this deshrinking using several techniques, whilst deshrinkPred will deshrink WA estimates for new samples given a set of deshrinking coefficients.

Usage

deshrink(env, wa.env,
         type = c("inverse", "classical", "expanded", "none",
                  "monotonic"))
deshrinkPred(x, coef,
         type = c("inverse", "classical", "expanded", "none",
                  "monotonic"))

Value

For deshrinkPred a numeric vector of deshrunk estimates.

For an object of class "deshrink", inheriting from class

"list", with two components. The type of deshrinking performed is stroed within attribute "type". The componets of the returned object are:

coefficients: The deshrinking coefficients used.
env: The deshrunk WA estimates.

Arguments

env: numeric; original environmental values.
wa.env: numeric; initial weighted average estimates.
type: character; the type of deshrinking. One of "inverse", "classical", "expand", "none".
x: numeric; estimates to be deshrunk.
coef: numeric; deshrinking coefficients to use. Currently needs to be a vector of length 2. These should be supplied in the order \(\beta_0,\beta_1\).

Author

Gavin L. Simpson & Jari Oksanen

Warning

deshrinkPred, does not currently check that the correct coefficients have been supplied in the correct order.

References

Birks, H.J.B. (1995) Quantitative environmental reconstructions. In Statistical modelling of Quaternary science data (eds.~D.Maddy & J.S. Brew). Quaternary Research Association technical guide 5. Quaternary Research Association, Cambridge.