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.
CC                      Fatty acid calibration coefficients.
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.
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()'.
POOLVARmeth             Computes within species variance-covariance
                        matrices on transformed scaled, along with a
                        pooled estimate.
QFASA                   QFASA: A package for Quantitative Fatty Acid
                        Signature Analysis
QFASA.const.eqn         Returns 'sum(alpha)' and used in 'solnp()'.
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.
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.
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.
mean_geometric          Returns the geometric mean of a compositional
                        vector
multiplicativeReplacement
                        Multiplicative replacement of zeroes
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.SMUFASA               Simultaneous maximum unified fatty acid
                        signature analysis
p.sim.QFASA             Simultaneous estimation of diet composition and
                        calibration coefficients
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.
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.
