Nothing
# wren tests
context("wrens")
test_that("wren 5 minute counts works",{
## standard five-minute counts
data(wren_5min)
cu_wren_5min <- 1/sqrt(10000)
w1_df_unif <- ds(wren_5min, transect="point", truncation=110, key="unif",
convert_units=cu_wren_5min, order=c(1,2), er_var="P3",
optimizer = "R")
# do the same thing with dht2
w1_nhat <- dht2(w1_df_unif, flatfile=wren_5min, strat_formula=~Region.Label,
convert_units=cu_wren_5min, er_est="P3")
d_stuff <- w1_df_unif$dht$individuals$D
expect_equal(attr(w1_nhat,"density")$Density, d_stuff$Estimate, tol=1e-3)
expect_equal(attr(w1_nhat,"density")$LCI, d_stuff$lcl, tol=1e-3)
expect_equal(attr(w1_nhat,"density")$UCI, d_stuff$ucl, tol=1e-3)
expect_equal(attr(w1_nhat,"density")$Density_se, d_stuff$se, tol=1e-3)
expect_equal(attr(w1_nhat,"density")$Density_CV, d_stuff$cv, tol=1e-3)
})
test_that("wren snapshot works",{
## the ‘snapshot’ method
data(wren_snapshot)
cu_wren_snapshot <- 1/sqrt(10000)
w2_df_hr <- ds(wren_snapshot, transect="point", truncation=110, key="hr",
adjustment=NULL, convert_units=cu_wren_snapshot, er_var="P3")
w2_nhat <- dht2(w2_df_hr, flatfile=wren_snapshot, strat_formula=~Region.Label,
convert_units=cu_wren_snapshot, er_est="P3")
d_stuff <- w2_df_hr$dht$individuals$D
expect_equal(attr(w2_nhat,"density")$n, w2_df_hr$dht$individuals$summary$n)
expect_equal(attr(w2_nhat,"density")$k, w2_df_hr$dht$individuals$summary$k[1])
expect_equal(attr(w2_nhat,"density")$Effort, w2_df_hr$dht$individuals$summary$Effort)
expect_equal(attr(w2_nhat,"density")$Covered_area,
w2_df_hr$dht$individuals$summary$CoveredArea)
expect_equal(attr(w2_nhat,"density")$Density, d_stuff$Estimate, tol=1e-3)
expect_equal(attr(w2_nhat,"density")$LCI, d_stuff$lcl, tol=1e-3)
expect_equal(attr(w2_nhat,"density")$UCI, d_stuff$ucl, tol=1e-3)
expect_equal(attr(w2_nhat,"density")$Density_se, d_stuff$se, tol=1e-6)
expect_equal(attr(w2_nhat,"density")$Density_CV, d_stuff$cv, tol=1e-3)
})
test_that("wren cue count works",{
## cue count method
data(wren_cuecount)
mult <- unique(wren_cuecount[, c("Cue.rate","Cue.rate.SE")])
names(mult) <- c("rate", "SE")
# search time is the effort
wren_cuecount$Effort <- wren_cuecount$Search.time
# for comparability with distance, we ignore replicate visits
wren_cuecount$Sample.Label_old <- wren_cuecount$Sample.Label
wren_cuecount$Sample.Label <- sub("-\\d+", "", wren_cuecount$Sample.Label)
cu <- sqrt(0.0001)
w3_df_hr <- ds(wren_cuecount, transect="point", truncation=92.5,
adjustment=NULL, key="hr", er_var="P3", convert_units=cu)
w3_nhat <- dht2(w3_df_hr, flatfile=wren_cuecount, strat_formula=~Region.Label,
multipliers=list(creation=mult), convert_units=cu, er_est="P3")
expect_equal(w3_nhat$Abundance_se, 8.0002, tol=1e-2)
expect_equal(attr(w3_nhat,"density")$Density, 1.2123, tol=1e-1)
expect_equal(attr(w3_nhat,"density")$Density_se, 0.24262, tol=1e-2)
expect_equal(attr(w3_nhat,"density")$Density_CV, .2001, tol=1e-2)
expect_equal(attr(w3_nhat,"density")$LCI, 0.82134, tol=1e-2)
expect_equal(attr(w3_nhat,"density")$UCI, 1.7893, tol=1e-2)
})
#test_that("wren 4 works",{
# ## line transect data
# data(wren4)
#
# cu <- (1/1000)*1/0.01
# # cribbed the best model
# w4_df_hn <- ds(wren4, transect="line", truncation=95, key="hn",
# adjustment=NULL, convert.units=cu)
#
#
# result <- ddf(dsmodel = ~mcds(key = "hn", formula = ~1, adj.series="herm", adj.order=c(4,6)),
# data = w4_df_hn$ddf$data, method = "ds",
# meta.data = list(width = 95),
# control=list(initial=list(scale=log(.3532E5), adjust=c(.1184E6, .1534E5)),
# nofit=TRUE))
#
#
# w4_nhat <- dht2(result, flatfile=wren4, strat_formula=~Region.Label,
# convert_units=cu)
# expect_equal(attr(w4_nhat,"density")$Density, 2.1344, tol=1e-1)
# expect_equal(attr(w4_nhat,"density")$Density_se, 0.21949, tol=1e-2)
# expect_equal(attr(w4_nhat,"density")$Density_CV, .1028, tol=1e-2)
# expect_equal(attr(w4_nhat,"density")$LCI, 1.7382, tol=1e-2)
# expect_equal(attr(w4_nhat,"density")$UCI, 2.6207, tol=1e-2)
#})
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