# Quantitative Fatty Acid Signature Analysis

## Documentation for package ‘QFASA’ version 1.2.1

- 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
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.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.