pGLS (version 0.0-1)

pGLS: An Generalized Least Square model for comparative Phylogenetics

Description

pGLS An Generalized Least Square model for Comparative Phylogenetics

Usage

pGLS(formula,data,covarmatrix,na.action, intercept = TRUE)

Arguments

formula
a formula describing the model to be fit. Note, that an intercept is included at default.
data
the data frame including the predictors (X's) and the response (Y)
covarmatrix
the var-covariance matrix that is derived from phylogeny or other sources
na.action
a dummy term for data cleaning.
intercept
TRUE (default) if the specified model is with a intercept. It is rare to fit a such model without intercepts.

Value

A list object of class "z" containing the results of GLS fitting. The components are:
pred
fitted values and standard errors of the fitted values.
coefficients
estimated coefficients.
cov.coeff
estimated covariance matrix of the coefficients
"sigma^2"
estimated variance
pred.cond.
(for unknown species only)predicted y-values conditioning on the known species. Note if there are no unknown species present in the data, conditional prediction is not calculated.
R-Sq
fraction of total variance explained by the GLS model

References

Garland, T., Jr., and A. R. Ives. (2000) Using the past to predict the present: Confidence intervals for regression equations in phylogenetic comparative methods. American Naturalist 155:346-364.

Martins, E. P., and T. F. Hansen. (1996) The statistical analysis of interspecific data: a review and evaluation of comparative methods. Pages 22-75 in E. P. Martins, ed. Phylogenies and the comparative method in animal behavior. Oxford University Press, Oxford.

Box, G. E. P., G. M. Jenkins, and G. C. Reinsel. (1994) Pages 282-285 Time series analysis: forecasting and control. Prentice Hall, Englewood Cliffs, N.J.

Anderson, T.W. (2003). An Introduction to Multivariate Statistical Analysis. Wiley-Interscience; 3rd edition

Examples

Run this code
data(pGLS)
pGLS(logAGIL~logBM+logASCR,data_fs,var_fs,na.pass)

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