calc.betas: Calculate Beta Coefficients for Predictions

In morphErr: Measurement Error Models for Morphometric Data

Calculate Beta Coefficients for Predictions

Description

Calculates coefficients for predicting one dimension from others, using either linear model or PCA interpretation.

Usage

calc.betas(
  fit,
  est = NULL,
  stders = TRUE,
  y.dim,
  x.dim,
  type = "lm",
  vcov = FALSE
)

Arguments

fit	A fitted model object of class "lme.morph"
est	Optional parameter estimates (if NULL, extracted from fit)
stders	Logical; whether to compute standard errors
y.dim	Integer specifying which dimension to predict
x.dim	Integer vector specifying which dimensions to use as predictors
type	Character string, either "lm" or "pca"
vcov	Logical; if TRUE, returns variance-covariance matrix

Value

If vcov = FALSE, a matrix with estimates and standard errors. If vcov = TRUE, a list with components:

est	Vector of coefficient estimates
varcov	Variance-covariance matrix

morphErr documentation built on Aug. 30, 2026, 5:06 p.m.