From 74c72f2d286a8bfec88419cb8a6b449dd1cdf106 Mon Sep 17 00:00:00 2001 From: smishr <43640926+smishr@users.noreply.github.com> Date: Mon, 10 Apr 2023 11:14:26 +0530 Subject: [PATCH] Add Vector{Symbol} test Domain est --- test/total.jl | 43 ++++++++++++++++++++++++++++++++++++++++++- 1 file changed, 42 insertions(+), 1 deletion(-) diff --git a/test/total.jl b/test/total.jl index fc02b48f..b7780263 100644 --- a/test/total.jl +++ b/test/total.jl @@ -171,7 +171,9 @@ end # Test multiple domains passed at once tot = total(:api00, [:stype,:cname], dclus1_boot) - + @test filter(row -> row[:cname] == "Los Angeles" && row[:stype] == "E", tot).SE[1] ≈ 343365 rtol = STAT_TOL + @test filter(row -> row[:cname] == "Merced" && row[:stype] == "H", tot).SE[1] ≈ 27090.33 rtol = STAT_TOL + #### Why doesnt this syntax produce domain estimates?? # Test that column specifiers from DataFrames make it through this pipeline # These tests replicate what you see above...just with a different syntax. @@ -183,3 +185,42 @@ end # @test filter(:cname => ==("San Diego"), tot).total[1] ≈ 1830375.53 rtol = STAT_TOL # @test filter(:cname => ==("San Diego"), tot).SE[1] ≈ 1298696.64 rtol = SE_TOL end + +#### R code for vector{Symbol} domain estimation +# > data(api) +# > apiclus1$pw = rep(757/15,nrow(apiclus1)) +# > ### 9.04.23 +# > dclus1<-svydesign(id=~dnum, weights=~pw, data=apiclus1); +# > rclus1<-as.svrepdesign(dclus1, type="subbootstrap", compress=FALSE, replicates = 4000) +# > svyby(~api00, ~stype+cname, rclus1, svytotal) +# stype cname api00 se +# E.Alameda E Alameda 273428.40 275423.33 +# H.Alameda H Alameda 30683.73 30907.60 +# M.Alameda M Alameda 67272.07 67762.88 +# E.Fresno E Fresno 48599.40 47484.67 +# H.Fresno H Fresno 22356.73 21843.93 +# M.Fresno M Fresno 24324.93 23766.99 +# E.Kern E Kern 24930.53 24847.76 +# M.Kern M Kern 20741.80 20672.93 +# E.Los Angeles E Los Angeles 395154.00 341692.92 +# M.Los Angeles M Los Angeles 94826.87 95416.42 +# E.Mendocino E Mendocino 58844.13 57711.15 +# H.Mendocino H Mendocino 35124.80 34448.51 +# M.Mendocino M Mendocino 31844.47 31231.33 +# E.Merced E Merced 50517.13 51424.65 +# H.Merced H Merced 26696.87 27176.47 +# M.Merced M Merced 27605.27 28101.18 +# E.Orange E Orange 463536.33 465047.76 +# M.Orange M Orange 110219.20 110578.59 +# E.Plumas E Plumas 144284.20 146672.86 +# H.Plumas H Plumas 143729.07 146108.54 +# M.Plumas M Plumas 34266.87 34834.16 +# E.San Diego E San Diego 1670497.13 1233144.04 +# H.San Diego H San Diego 63386.13 63693.54 +# M.San Diego M San Diego 96492.27 96960.22 +# E.San Joaquin E San Joaquin 848243.73 848605.33 +# H.San Joaquin H San Joaquin 79585.93 79619.86 +# M.San Joaquin M San Joaquin 101387.53 101430.75 +# E.Santa Clara E Santa Clara 737418.93 484164.71 +# H.Santa Clara H Santa Clara 35478.07 35311.28 +# M.Santa Clara M Santa Clara 187685.53 131278.63 \ No newline at end of file