compute.links.from.reals: Compute link values from real parameters

In RMark: R Code for Mark Analysis

Compute link values from real parameters

Description

Computes link values from reals using 1-1 real to beta(=link) transformation. Also, creates a v-c matrix for the link values if vcv.real is specified.

Usage

compute.links.from.reals(
  x,
  model,
  parm.indices = NULL,
  vcv.real = NULL,
  use.mlogits = TRUE
)

Arguments

x	vector of real estimates to be converted to link values
model	MARK model object used only to obtain model structure/links etc. If function is being called for model averaged estimates, then any model in the model list used to construct the estimates is sufficient
parm.indices	index numbers from PIMS for rows in design matrix(non-simplified indices); x[parm.indices] are computed
vcv.real	v-c matrix for the real parameters
use.mlogits	logical; if FALSE then parameters with mlogit links are transformed with logit rather than mlogit for creating confidence intervals for each value

Details

It has 2 uses both related to model averaged estimates. Firstly, it is used to transform model averaged estimates so the normal confidence interval can be constructed on the link values and then back-transformed to real space. The second function is to enable parametric bootstrapping in which the error distbution is assumed to be multivariate normal for the link values. From a single model, the link values are easily constructed from the betas and design matrix so this function is not needed. But for model averaging there is no equivalent because the real parameters are averaged over a variety of models with the same real parameter structure but differing design structures. This function allows for link values and their var-cov matrix to be created from the model averaged real estimates.

Value

A list with the estimates (link values) and the links that were used. If vcv.real = TRUE, then the v-c matrix of the links is also returned.

Author(s)

Jeff Laake

See Also

model.average

RMark documentation built on Aug. 14, 2022, 1:05 a.m.