Nothing
# test Satterthwaite degrees of freedom calculation
context("Satterthwaite degrees of freedom")
tol <- 1e-3
test_that("group size, no strat", {
# add group sizes to minke
groupsizes <- c(1, 1, 2, 4, 2, 6, 1, 3, 2, 5, 1, 2, 3, 2, 2, 1, 1, 2, 1, 2, 1,
1, 2, 2, NA, NA, 2, 2, 11, 1, 1, 2, NA, NA, NA, NA, 1, 1, 2, 2,
1, 2, 2, 2, 2, 1, 8, 10, 5, 7, 3, 1, 2, 2, 2, 10, 1, 1, 2, 2, 1,
2, NA, 2, 2, 2, 1, 1, 1, 1, 1, 1, 2, 3, 1, 1, 2, 3, 2, 1, 2, 1,
10, 1, 7, 2, 1, 1, 1, 1, 3, 1, NA, 1, 1, 1, 1, 1, NA)
data(minke)
minke$Region.Label <- "same"
minke$Area <- 1000000
minke$size <- groupsizes
minke$object <- NA
minke$object[!is.na(minke$distance)] <- 1:sum(!is.na(minke$distance))
# fit and test dht
simple <- ds(minke, key="hr", truncation=1.5, er_method=1, adjustment=NULL)
expect_equal(simple$dht$individuals$D$Estimate, 0.57542E-01, tol=tol)
expect_equal(simple$dht$clusters$D$Estimate, 0.25574E-01, tol=tol)
expect_equal(simple$dht$individuals$D$df, 45.44, tol=tol)
expect_equal(simple$dht$clusters$D$df, 34.49, tol=tol)
expect_equal(simple$dht$individuals$D$cv, 27.89/100, tol=tol)
expect_equal(simple$dht$clusters$D$cv, 25.98/100, tol=tol)
# now with dht2
d2 <- dht2(simple, flatfile=minke, strat_formula=~1, innes=FALSE)
den_res <- attr(d2, "density")
expect_equal(den_res$Density, 0.57542E-01, tol=tol)
expect_equal(den_res$df, 45.44, tol=tol)
expect_equal(den_res$Density_CV, 27.89/100, tol=tol)
gr_den_res <- attr(attr(d2, "grouped"), "density")
expect_equal(gr_den_res$Density, 0.25574E-01, tol=tol)
expect_equal(gr_den_res$df, 34.49, tol=tol)
expect_equal(gr_den_res$Density_CV, 25.98/100, tol=tol)
# distance results
# Effort : 1842.790
# # samples : 25
# Width : 1.500000
# # observations: 88
#
# Model 1
# Hazard Rate key, k(y) = 1 - Exp(-(y/A(1))**-A(2))
#
#
# Point Standard Percent Coef. 95% Percent
# Parameter Estimate Error of Variation Confidence Interval
# --------- ----------- ----------- -------------- ----------------------
# DS 0.25574E-01 0.66433E-02 25.98 0.15219E-01 0.42975E-01
# E(S) 2.2500 0.22872 10.17 1.8393 2.7524
# D 0.57542E-01 0.16051E-01 27.89 0.33159E-01 0.99853E-01
# N 41161. 11482. 27.89 23719. 71427.
# --------- ----------- ----------- -------------- ----------------------
#
# Measurement Units
# ---------------------------------
# Density: Numbers/Sq. kilometers
# ESW: kilometers
#
# Component Percentages of Var(D)
# -------------------------------
# Detection probability : 14.8
# Encounter rate : 71.9
# Cluster size : 13.3
# Estimate %CV df 95% Confidence Interval
# ------------------------------------------------------
# Hazard/Cosine
# DS 0.25574E-01 25.98 34.49 0.15219E-01 0.42975E-01
# D 0.57542E-01 27.89 45.44 0.33159E-01 0.99853E-01
# N 41161. 27.89 45.44 23719. 71427.
})
test_that("stratification works", {
groupsizes <- c(1, 1, 2, 4, 2, 6, 1, 3, 2, 5, 1, 2, 3, 2, 2, 1, 1, 2, 1, 2,
1, 1, 2, 2, NA, NA, 2, 2, 11, 1, 1, 2, NA, NA, NA, NA, 1, 1, 2,
2, 1, 2, 2, 2, 2, 1, 8, 10, 5, 7, 3, 1, 2, 2, 2, 10, 1, 1, 2,
2, 1, 2, NA, 2, 2, 2, 1, 1, 1, 1, 1, 1, 2, 3, 1, 1, 2, 3, 2, 1,
2, 1, 10, 1, 7, 2, 1, 1, 1, 1, 3, 1, NA, 1, 1, 1, 1, 1, NA)
data(minke)
minke$size <- groupsizes
minke$object <- NA
minke$object[!is.na(minke$distance)] <- 1:sum(!is.na(minke$distance))
simple2 <- ds(minke, key="hr", truncation=1.5, er_method=1, adjustment=NULL)
expect_equal(simple2$dht$individuals$D$Estimate,
c(0.44945E-01, 0.92867E-01, 0.50621E-01), tol=tol)
expect_equal(simple2$dht$clusters$D$Estimate,
c(0.19318E-01, 0.43117E-01, 0.22137E-01), tol=tol)
expect_equal(simple2$dht$individuals$D$df, c(17.01, 28.87, 19.64), tol=1e-2)
expect_equal(simple2$dht$clusters$D$df, c(12.97, 17.96, 15.26), tol=tol)
expect_equal(simple2$dht$individuals$D$cv, c(40.82, 28.33, 33.13)/100, tol=tol)
expect_equal(simple2$dht$clusters$D$cv, c(38.08, 24.91, 30.53)/100, tol=tol)
# now with dht2
d2 <- dht2(simple2, flatfile=minke, strat_formula=~Region.Label, innes=FALSE)
den_res <- attr(d2, "density")
expect_equal(den_res$Density,
c(0.44945E-01, 0.92867E-01, 0.50621E-01), tol=tol)
expect_equal(den_res$df, c(17.01, 28.87, 19.64), tol=1e-2)
expect_equal(den_res$Density_CV, c(40.82, 28.33, 33.13)/100, tol=1e-2)
gr_den_res <- attr(attr(d2, "grouped"), "density")
expect_equal(gr_den_res$Density,
c(0.19318E-01, 0.43117E-01, 0.22137E-01), tol=tol)
expect_equal(gr_den_res$df, c(12.97, 17.96, 15.26), tol=tol)
expect_equal(gr_den_res$Density_CV, c(38.08, 24.91, 30.53)/100, tol=1e-2)
# Estimate %CV df 95% Confidence Interval
# ------------------------------------------------------
# Stratum: North
# Hazard/Cosine
# DS 0.19318E-01 38.08 12.97 0.87222E-02 0.42787E-01
# D 0.44945E-01 40.82 17.01 0.19635E-01 0.10288
# N 28341. 40.82 17.01 12381. 64874.
# Stratum: South
# Hazard/Cosine
# DS 0.43117E-01 24.91 17.96 0.25747E-01 0.72205E-01
# D 0.92867E-01 28.33 28.87 0.52604E-01 0.16394
# N 7869.0 28.33 28.87 4457.0 13892.
#
#
# Pooled Estimates:
# Estimate %CV df 95% Confidence Interval
# ------------------------------------------------------
# DS 0.22137E-01 30.53 15.26 0.11727E-01 0.41789E-01
# D 0.50621E-01 33.13 19.64 0.25800E-01 0.99321E-01
# N 36210. 33.13 19.64 18455. 71046.
})
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