Description Usage Arguments Value Author(s) See Also Examples
View source: R/estimate.shiftvec.R
Given two data frames, one containing isotopic measurements from some
predator species, and another containing isotopic measurements from a
collection of prey species, return num.samples
samples of
discrimination factors from predators to prey.
1 2 | estimate.shiftvec(predator, prey, num.samples=1000, num.preysamples=1,
pred.distinput=FALSE, prey.distinput=TRUE)
|
predator |
A data frame containing the isotopic measurements (presented as raw data or mean/standard deviation) from a predator species. |
prey |
A data frame containing the isotopic measurements (presented as raw data or mean/standard deviation) from a prey species. |
num.samples |
The number of samples of discrimination factors to produce. |
num.preysamples |
The number of samples to draw from each prey source when performing the estimation process. |
pred.distinput |
|
prey.distinput |
|
A matrix with num.samples
rows, each of which contains one
estimate discrimination factor.
Robert Robere
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 | ## normally input is read from a file via build.isotopeframe, but here
## we generate the input by hand
## we have three prey species: birds, mice, and bugs
## one predator species: cats
## we are measuring two isotopic values for each: %%C and %%N
## assume that all measurements are normally distributed
bird.samples <- as.data.frame(mvrnorm(n=25, mu=c(2, 2),
Sigma=diag(c(1, 1), nrow=2)))
mice.samples <- as.data.frame(mvrnorm(n=25, mu=c(4, 4),
Sigma=diag(c(1, 1), nrow=2)))
bugs.samples <- as.data.frame(mvrnorm(n=25, mu=c(2, 6),
Sigma=diag(c(1, 1), nrow=2)))
## note that prey are collected into a single data frame,
## as are the predators
## if number of samples differs from species to species,
## the data frame should be padded
## with NAs appropriately (this is done automatically when
## reading in from CSV)
pred.frame <- data.frame(cats=mvrnorm(n=20, mu=c(6, 6),
Sigma=diag(c(1/2, 1/2), nrow=2)))
prey.frame = data.frame(bird=bird.samples, mice=mice.samples,
bugs=bugs.samples)
## now estimate discrimination factors
## in applications, usually the prey measurements are given by mean/sd
## of corresponding gaussian, so we notify the function that we are
## actually providing samples in this example
estimate.shiftvec(pred.frame, prey.frame, num.samples=10,
prey.distinput=FALSE)
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