varlog.lam | R Documentation |
Calculates the variance of the log rate of change between 2 population estimates that rely on the same sightability model.
varlog.lam(sight1, sight2)
sight1 |
Sightability model object for the first population estimate (formed by calling Sight.Est function) |
sight2 |
Sightability model object for the second population estimate (formed by calling Sight.Est function) |
This function uses the delta method to calculate an approximate variance for the log rate of change, log(tau^[t+1])-log(tau^[t]), while accounting for the positive covariance between the two estimates (as a result of using the same sightability model to correct for detection).
loglambda |
log rate of change = log(tau^[t+1]/tau^[t]) |
varloglamda |
approximate variance of loglambda |
John Fieberg
vardiff
# Example using moose survey data
data(obs.m) # observational moose survey data
data(exp.m) # experimental moose survey data
data(sampinfo.m) # information on sampling rates
# Estimate population size in 2006 and 2007
sampinfo <- sampinfo.m[sampinfo.m$year==2007, ]
tau.2007 <- Sight.Est(observed ~ voc, odat = obs.m[obs.m$year==2007, ],
sdat = exp.m, sampinfo.m[sampinfo.m$year == 2007, ],
method = "Wong", logCI = TRUE, alpha = 0.05, Vm.boot = FALSE)
tau.2006 <- Sight.Est(observed ~ voc, odat = obs.m[obs.m$year==2006, ],
sdat = exp.m, sampinfo.m[sampinfo.m$year == 2006, ],
method = "Wong", logCI = TRUE, alpha = 0.05, Vm.boot = FALSE)
# Log rate of change
varlog.lam(tau.2006, tau.2007)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.