Quantitative Fatty Acid Signature Analysis

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Documentation for package ‘QFASA’ version 1.2.0

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

QFASA-package	QFASA: A package for Quantitative Fatty Acid Signature Analysis
AIT.dist	Returns the distance between two compositional vectors using Aitchison's distance measure.
AIT.more	Used to provide additional information on various model components evaluated at the optimal solution, i.e., using the QFASA diet estimates and Aitchison distance measure.
AIT.obj	Used in 'solnp()' as the objective function to be minimized when Aitchison distance measure is chosen.
backward.elimination	Returns diet estimates corresponding to a sample of predators based on a backward elimination algorithm that chooses the prey species to be included in the modelling.
bal.diet.data	Sample example of balanced repeatability diet estimates data with only two repeated measurements per predator.
CC	Fatty acid calibration coefficients.
chisq.CA	Called by 'create.d.mat()' to compute the chi-square distance.
chisq.dist	Returns the distance between two compositional vectors using the chi-square distance.
comp.rep	Repeatability in Diet Estimates
conf.meth	Confidence Intervals for Diet Proportions
create.d.mat	Called by 'testfordiff.ind.boot.fun()' to create a matrix of distances.
CS.more	Used to provide additional information on various model components evaluated at the optimal solution, i.e., using the QFASA diet estimates and chi-square distance measure.
CS.obj	Used in 'solnp()' as the objective function to be minimized when chi-square distance measure is chosen. Unlike 'AIT.obj()' and 'KL.obj()', does not require modifying zeros.
FAset	List of fatty acids used in sample prey and predator data sets, 'preyFAs' and 'predatorFAs' respectively.
forward.selection	Returns diet estimates corresponding to a sample of predators based on a forward selection algorithm that chooses the prey species to be included in the modelling.
KL.dist	Returns the distance between two compositional vectors using Kullback-Leibler distance measure.
KL.more	Used to provide additional information on various model components evaluated at the optimal solution, i.e., using the QFASA diet estimates and Kullback-Leibler distance measure.
KL.obj	Used in 'solnp()' as the objective function to be minimized when Kullback-Leibler distance measure is chosen.
MEANmeth	Returns the multivariate mean FA signature of each prey group entered into the QFASA model. Result can be passed to prey.mat in 'p.QFASA()'.
mean_geometric	Returns the geometric mean of a compositional vector
p.MLE	Returns simplified MLE diet estimates corresponding to a sample of predators.
p.MUFASA	Returns MUFASA diet estimates corresponding to a sample of predators.
p.QFASA	Returns QFASA diet estimates corresponding to a sample of predators.
p.sim.QFASA	Simultaneous estimation of diet composition and calibration coefficients
p.SMUFASA	Simultaneous maximum unified fatty acid signature analysis
POOLVARmeth	Computes within species variance-covariance matrices on transformed scaled, along with a pooled estimate.
predatorFAs	Predator fatty acid signatures. Each predator signature is a row with fatty acid proportions in columns.
prey.cluster	Produces a dendrogram using distances between the mean FA signatures of the prey types.
prey.on.prey	Each prey fatty acid signature is systematically removed from the supplied prey database and its QFASA diet estimate is obtained by treating the individual as a predator.
preyFAs	Prey fatty acid signatures. Each prey signature is a row with fatty acid proportions in columns.
pseudo.pred	Generate a pseudo predator by sampling with replacement from prey database.
pseudo.pred.norm	Generate a pseudo predator parametrically from multivariate normal distributions.
QFASA	QFASA: A package for Quantitative Fatty Acid Signature Analysis
QFASA.const.eqn	Returns 'sum(alpha)' and used in 'solnp()'.
split_prey	Splits prey database into a simulation set (1/3) and a modelling set (2/3). Returns a list:
testfordiff.ind.boot	Called by 'testfordiff.ind.pval()'.
testfordiff.ind.boot.fun	Called by 'testfordiff.ind.boot()'.
testfordiff.ind.pval	Test for a difference between two independent samples of compositional data. Zeros of any type are allowed.
unbal.diet.data	Sample example of unbalanced repeatability diet estimates data with a max of two repeated measurements per predator.