calc.gpe2: Calculate Light Likelihood from GPE2 Output

In HMMoce: Improved Analysis of Marine Animal Movement Data Using Hidden Markov Models

Description

calc.gpe2 calculates likelihood estimates for each day of animal tag data.

Usage

calc.gpe2(locs, locDates, locs.grid, dateVec, errEll = TRUE, gpeOnly = TRUE)

Arguments

locs	is data frame from -Locations file output from DAP/Tag Portal for WC tags and contains GPS, Argos, and GPE locations as applicable.
locDates	is vector of dates from locs dataframe
locs.grid	is list output from setup.locs.grid
dateVec	is vector of dates from tag to pop-up in 1 day increments.
errEll	is logical indicating whether error ellipses should be generated for light-based likelihoods as given from output of WC-GPE. False if only longitude should be used. If False, standard deviation on light measurements is currently fixed at 0.7 deg longitude following Musyl et al 2011. Default is FALSE and will use longitude only.
gpeOnly	is logical. If TRUE (default), locs input is trimmed to GPE positions only. This is most applicable in scenarios with FastGPS data and you're adding this as a GPS input.

Details

Light errors are parameterized using elliptical error values output in '-Locations.csv' (WC tags).

Value

L is an array of lon x lat likelihood surfaces (matrices) for each time point (3rd dimension)

References

Musyl MK, Domeier ML, Nasby-Lucas N, Brill RW, McNaughton LM, Swimmer JY, Lutcavage MS, Wilson SG, Galuardi B, Liddle JB (2011) Performance of pop-up satellite archival tags. Mar Ecol Prog Ser

See Also

calc.srss

Examples

## Setup for calculating light likelihood
# Read the data
locsFile <- system.file("extdata", "141259-Locations-GPE2.csv", package = "HMMoce")
locs <- read.table(locsFile, sep = ',', header = TRUE, blank.lines.skip = FALSE)

# Set spatial and temporal limits
sp.lim <- list(lonmin = -82, lonmax = -25, latmin = 15, latmax = 50)
locs.grid <- setup.locs.grid(sp.lim)
iniloc <- data.frame(matrix(c(13, 10, 2015, 41.3, -69.27, 10, 4, 2016, 40.251, -36.061),
 nrow = 2, ncol = 5, byrow = TRUE))
names(iniloc) <- list('day','month','year','lat','lon')
tag <- as.POSIXct(paste(iniloc[1,1], '/', iniloc[1,2], '/', iniloc[1,3], sep=''), 
format = '%d/%m/%Y', tz='UTC')
pop <- as.POSIXct(paste(iniloc[2,1], '/', iniloc[2,2], '/', iniloc[2,3], sep=''), 
format = '%d/%m/%Y', tz='UTC')
dateVec <- as.Date(seq(tag, pop, by = 'day')) 

# Try a calculation
L.light <- calc.gpe2(locs[1,], iniloc, locs.grid, dateVec, errEll=TRUE, gpeOnly=TRUE)

## Not run: 
# Full example light calculation
L.light <- calc.gpe2(locs, iniloc = iniloc, locs.grid = locs.grid,
                     dateVec = dateVec, errEll = TRUE, gpeOnly = TRUE)

## End(Not run)

HMMoce documentation built on Nov. 17, 2017, 5:57 a.m.