estimate.shiftvec

Description

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.

Usage

estimate.shiftvec(predator, prey, num.samples=1000, num.preysamples=1,
  pred.distinput=FALSE, prey.distinput=TRUE)

Arguments

Value

A matrix with num.samples rows, each of which contains one estimate discrimination factor.

Author(s)

Robert Robere

See Also

build.isotopeframe

Examples

## 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) 

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(EDFIR)
Loading required package: lpSolve
Loading required package: geometry
Loading required package: magic
Loading required package: abind
Loading required package: vertexenum
Loading required package: MASS
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/EDFIR/estimate.shiftvec.Rd_%03d_medium.png", width=480, height=480)
> ### Name: estimate.shiftvec
> ### Title: estimate.shiftvec
> ### Aliases: estimate.shiftvec
> 
> ### ** Examples
> 
> ## 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) 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>