QFASA (version 1.2.1)

bias.all: Calculate bias correction for confidence intervals from beta.meths.CI.

Description

Calculate bias correction for confidence intervals from beta.meths.CI.

Usage

bias.all(
  p.mat,
  prey.mat,
  cal.mat = rep(1, length(ext.fa)),
  fat.cont = rep(1, nrow(prey.mat)),
  R.bias,
  noise,
  nprey,
  specify.noise,
  dist.meas,
  ext.fa
)

Value

Row 1 is Lambda CI, row 2 is Lambda skew, and row 3 is Beta CI

Arguments

p.mat

matrix containing the fatty acid signatures of the predators.

prey.mat

matrix containing a representative fatty acid signature

cal.mat

matrix of calibration factors where the i th column is to be used with the i th predator. If modelling is to be done without calibration coefficients, simply pass a vector or matrix of ones.

fat.cont

prey fat content

R.bias

bootstrap replicates

noise

noise

nprey

number of prey

specify.noise

noise

dist.meas

distance measure

ext.fa

subset of FA's to use.

Examples

## Fatty Acids
data(FAset)
fa.set = as.vector(unlist(FAset))

## Predators
data(predatorFAs)
tombstone.info = predatorFAs[,1:4]
predator.matrix = predatorFAs[, fa.set]
npredators = nrow(predator.matrix)

## Prey
prey.sub = preyFAs[, fa.set]
prey.sub = prey.sub / apply(prey.sub, 1, sum)
group = as.vector(preyFAs$Species)
prey.matrix.full = cbind(group,prey.sub)
prey.matrix = MEANmeth(prey.matrix.full)

## Calibration Coefficients
data(CC)
cal.vec = CC[CC$FA %in% fa.set, 2]
cal.mat = replicate(npredators, cal.vec)

# Note: uncomment examples to run. CRAN tests fail because execution time > 5 seconds
# diet.est <- p.QFASA(predator.mat = predator.matrix,
#                     prey.mat = prey.matrix,
#                     cal.mat = cal.mat,
#                     dist.meas = 2,
#                     start.val = rep(1,nrow(prey.matrix)),
#                     ext.fa = fa.set)[['Diet Estimates']]
#
# bias <- bias.all(p.mat = diet.est,
#                  prey.mat = prey.matrix.full,
#                  cal.mat = cal.mat,
#                  R.bias = 10,
#                  noise = 0,
#                  nprey = 50,
#                  dist.meas = 2,
#                  ext.fa = fa.set)