summary.lme.morph: Summarise Morphometric Model Fits

In morphErr: Measurement Error Models for Morphometric Data

Summarise Morphometric Model Fits

Description

An S3 method that creates summaries of fitted morphometric models. This function can provide different types of summaries including parameter estimates, beta coefficients, and tests for isometry.

Usage

## S3 method for class 'lme.morph'
summary(object, ..., type = "pars", y.dim, x.dim, level = 0.95)

Arguments

object	An object of class lme.morph, returned by fit.morph().
...	Other parameters (for S3 generic compatibility).
type	A character string specifying type of summary. Either "pars" (the default), "betas" "betas-lm", "betas-pca", or "isometric-pca". See 'Details' for further information.
y.dim	An integer specifying the response dimension for when type is "betas", "betas-lm", or "betas-pca".
x.dim	An integer vector specifying the explanatory dimensions for when type is "betas", "betas-lm", or "betas-pca".
level	The confidence level for any interval estimates.

Details

The following summaries are available with this method, controlled by the type argument:

type = "pars"

Estimates and standard errors for the model parameters, including the vectors \mu for the means of the true dimension sizes, \sigma for the standard deviations for true dimension sizes, \rho for the correlations between true dimension sizes, \psi for the standard deviations in measurement errors for the dimensions, and \phi for the correlations between measurement errors for all pairs of dimensions.

type = "betas" or type = "betas-lm"

Estimates and standard errors for coefficients of a linear combination that provides the expected value of one dimension (specified by y.dim) using any subset of the remaining dimensions (specified in the vector x.dim).

type = "betas-pca"

An estimated intercept and slope for the reduced major axis (or principal component axis) summarising the relationship between the true values of dimensions specified by y.dim and x.dim.

type = "isometric-pca"

Results for tests of the null hypotheses of isometric relationships between all pairs of dimensions. The p-values are obtained using normal approximations for the test statistics.

For models with log.transform = FALSE, the test statistic to test for isometric growth between dimensions p and q is \mu_p\sigma_q - \mu_q\sigma_p, which is equal to 0 under the null hypothesis.

For models with log.transform = TRUE, the test statistic is the slope for the reduced major axis (or principal component axis) summarising the relationship between the two dimensions, which is equal to 1 under the null hypothesis.

Value

A matrix or data frame containing the requested summary.

Examples

## Fitting model to manta ray data.
fit <- fit.morph(manta)
## Parameter estimates and standard errors.
summary(fit)
## Estimated coefficients for the linear combination that provides
## the expected value of the first dimension from only the second.
summary(fit, type = "betas-lm", y.dim = 1, x.dim = 2)
## Estimated coefficients for the linear combination that provides
## the expected value of the second dimension from both the first
## and third.
summary(fit, type = "betas-lm", y.dim = 2, x.dim = c(1, 3))
## Estimated intercept and slope for the reduced major axis (or
## pricipal component axis) summarising the relationship between
## the first and second dimensions.
summary(fit, type = "betas-pca", y.dim = 1, x.dim = 2)
## Tests for isometry between all pairs of dimensions.
summary(fit, type = "isometric-pca")

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