R/get_fitted.R
get_fitted.Rdget_fitted returns df of observed bycatch estimates (lambda of Poisson), accounting for effort but not accounting for observer coverage
get_fitted(fitted_model, alpha = 0.05, by_stream = FALSE)Data and fitted model returned from fit_bycatch(). If a hurdle model, then the plot returns the total bycatch rate (including zero and non-zero components).
The alpha level for the credible interval, defaults to 0.05
For multi-stream models, return fitted values by stream? Default FALSE (returns by year)
plot called from ggplot
# \donttest{
d <- data.frame(
"Year" = 2002:2014,
"Takes" = c(0, 0, 0, 0, 0, 0, 0, 0, 1, 3, 0, 0, 0),
"expansionRate" = c(24, 22, 14, 32, 28, 25, 30, 7, 26, 21, 22, 23, 27),
"Sets" = c(391, 340, 330, 660, 470, 500, 330, 287, 756, 673, 532, 351, 486)
)
fit <- fit_bycatch(Takes ~ 1,
data = d, time = "Year", effort = "Sets",
family = "poisson", time_varying = FALSE
)
#>
#> SAMPLING FOR MODEL 'bycatch' NOW (CHAIN 1).
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get_fitted(fit)
#> time mean low high obs
#> 1 2002 0.2801336 0.08470884 0.6026678 0
#> 2 2003 0.2435944 0.07365986 0.5240589 0
#> 3 2004 0.2364299 0.07149340 0.5086454 0
#> 4 2005 0.4728597 0.14298679 1.0172909 0
#> 5 2006 0.3367335 0.10182393 0.7244344 0
#> 6 2007 0.3582271 0.10832333 0.7706749 0
#> 7 2008 0.2364299 0.07149340 0.5086454 0
#> 8 2009 0.2056223 0.06217759 0.4423674 0
#> 9 2010 0.5416393 0.16378487 1.1652605 1
#> 10 2011 0.4821736 0.14580320 1.0373284 3
#> 11 2012 0.3811536 0.11525602 0.8199981 0
#> 12 2013 0.2514754 0.07604298 0.5410138 0
#> 13 2014 0.3481967 0.10529027 0.7490960 0
# }