LP_BTSPAS_est {Petersen}

Extract estimates of abundance after BTSPAS fit

Description

This will take a previous fit and return estimates of abundance.

Usage

LP_BTSPAS_est(LP_BTSPAS_fit, parm = "Ntot", conf_level = 0.95, trace = FALSE)

Arguments

LP_BTSPAS_fit

A result of an call to fitting at BTSPAS object.

parm

Which parameter from the BTSPAS fix is to be extracted?

conf_level

The expected coverage for confidence intervals on N.

trace

If trace flag is set in call when estimating functions

Value

An list object of class LP_BTSPAS_est with the following elements

• summary A data frame with the estimates of abundance, SE, and CI

• datetime Date and time the fit was done

Author(s)

Schwarz, C. J. [e-mail].

Examples

# NOTE. To keep execution time to a small value as required by CRAN
# I've made a very small example.
# Additionally, I've set the number of MCMC chains, iterations, burning, simulation to save to
# small values. Proper mixing may not have occurred yet.
# When using this routine, you likely want to the use the default values
# for these MCMC parameters.

data(data_btspas_diag1)
# extract the strata of interest
temp<- cbind(data_btspas_diag1,
             split_cap_hist( data_btspas_diag1$cap_hist,
                             sep="..", make.numeric=TRUE))
# only use data up to week 10 to keep example small
temp <- temp[ temp$t1 %in% 0:10 & temp$t2 %in% 0:10,]

fit <- Petersen::LP_BTSPAS_fit_Diag(
  temp,
  p_model=~1,
  InitialSeed=23943242,
  # the number of chains and iterations are too small to be useful
  # they are set to a small number to pare execution time to <5 seconds for an example
  n.chains=2, n.iter=20000, n.burnin=1000, n.sims=100,
  quietly=TRUE
)
fit$summary

# now get the estimates of abundance
est <-  Petersen::LP_BTSPAS_est (fit)
est$summary