Updated variance( ) function #757
Annotations
10 errors and 2 warnings
|
src/ratio.jl#L6
doctest failure in ~/work/Survey.jl/Survey.jl/src/ratio.jl:6-17
```jldoctest
julia> apiclus1 = load_data("apiclus1");
julia> dclus1 = SurveyDesign(apiclus1; clusters = :dnum, weights = :pw);
julia> ratio(:api00, :enroll, dclus1)
1×1 DataFrame
Row │ ratio
│ Float64
─────┼─────────
1 │ 1.17182
```
Subexpression:
ratio(:api00, :enroll, dclus1)
Evaluated output:
ERROR: MethodError: no method matching ratio(::Symbol, ::Symbol, ::SurveyDesign)
Closest candidates are:
ratio(!Matched::Vector{Symbol}, ::Any, ::AbstractSurveyDesign)
@ Survey ~/work/Survey.jl/Survey.jl/src/ratio.jl:114
Stacktrace:
[1] top-level scope
@ none:1
Expected output:
1×1 DataFrame
Row │ ratio
│ Float64
─────┼─────────
1 │ 1.17182
diff =
Warning: Diff output requires color.
1×1 DataFrame
Row │ ratio
│ Float64
─────┼─────────
1 │ 1.17182ERROR: MethodError: no method matching ratio(::Symbol, ::Symbol, ::SurveyDesign)
Closest candidates are:
ratio(!Matched::Vector{Symbol}, ::Any, ::AbstractSurveyDesign)
@ Survey ~/work/Survey.jl/Survey.jl/src/ratio.jl:114
Stacktrace:
[1] top-level scope
@ none:1
|
|
src/ratio.jl#L45
doctest failure in ~/work/Survey.jl/Survey.jl/src/ratio.jl:45-53
```jldoctest; setup = :(using Survey, StatsBase; apiclus1 = load_data("apiclus1"); dclus1 = SurveyDesign(apiclus1; clusters = :dnum, weights = :pw); bclus1 = bootweights(dclus1);)
julia> ratio([:api00, :api99], bclus1)
1×2 DataFrame
Row │ estimator SE
│ Float64 Float64
─────┼───────────────────────
1 │ 1.06127 0.00672259
```
Subexpression:
ratio([:api00, :api99], bclus1)
Evaluated output:
1×2 DataFrame
Row │ estimator SE
│ Float64 Float64
─────┼───────────────────────
1 │ 1.06127 0.00672259
Expected output:
diff =
Warning: Diff output requires color.
1×2 DataFrame
Row │ estimator SE
│ Float64 Float64
─────┼───────────────────────
1 │ 1.06127 0.00672259
|
|
src/ratio.jl#L74
doctest failure in ~/work/Survey.jl/Survey.jl/src/ratio.jl:74-91
```jldoctest ratiolabel; setup = :(using Survey, StatsBase; apiclus1 = load_data("apiclus1"); dclus1 = SurveyDesign(apiclus1; clusters = :dnum, weights = :pw); bclus1 = dclus1 |> bootweights;)
julia> ratio([:api00, :api99], :cname, dclus1)
11×2 DataFrame
Row │ ratio cname
│ Float64 String15
─────┼──────────────────────
1 │ 1.09852 Alameda
2 │ 1.17779 Fresno
3 │ 1.11453 Kern
4 │ 1.06307 Los Angeles
5 │ 1.00565 Mendocino
6 │ 1.08121 Merced
7 │ 1.03628 Orange
8 │ 1.02127 Plumas
9 │ 1.06112 San Diego
10 │ 1.07331 San Joaquin
11 │ 1.05598 Santa Clara
```
Subexpression:
ratio([:api00, :api99], :cname, dclus1)
Evaluated output:
unique(group[!, domain]) = InlineStrings.String15["Alameda"]
unique(group[!, domain]) = InlineStrings.String15["Fresno"]
unique(group[!, domain]) = InlineStrings.String15["Kern"]
unique(group[!, domain]) = InlineStrings.String15["Los Angeles"]
unique(group[!, domain]) = InlineStrings.String15["Mendocino"]
unique(group[!, domain]) = InlineStrings.String15["Merced"]
unique(group[!, domain]) = InlineStrings.String15["Orange"]
unique(group[!, domain]) = InlineStrings.String15["Plumas"]
unique(group[!, domain]) = InlineStrings.String15["San Diego"]
unique(group[!, domain]) = InlineStrings.String15["San Joaquin"]
unique(group[!, domain]) = InlineStrings.String15["Santa Clara"]
11×2 DataFrame
Row │ ratio cname
│ Float64 String15
─────┼──────────────────────
1 │ 1.09852 Alameda
2 │ 1.17779 Fresno
3 │ 1.11453 Kern
4 │ 1.06307 Los Angeles
5 │ 1.00565 Mendocino
6 │ 1.08121 Merced
7 │ 1.03628 Orange
8 │ 1.02127 Plumas
9 │ 1.06112 San Diego
10 │ 1.07331 San Joaquin
11 │ 1.05598 Santa Clara
Expected output:
11×2 DataFrame
Row │ ratio cname
│ Float64 String15
─────┼──────────────────────
1 │ 1.09852 Alameda
2 │ 1.17779 Fresno
3 │ 1.11453 Kern
4 │ 1.06307 Los Angeles
5 │ 1.00565 Mendocino
6 │ 1.08121 Merced
7 │ 1.03628 Orange
8 │ 1.02127 Plumas
9 │ 1.06112 San Diego
10 │ 1.07331 San Joaquin
11 │ 1.05598 Santa Clara
diff =
Warning: Diff output requires color.
unique(group[!, domain]) = InlineStrings.String15["Alameda"]
unique(group[!, domain]) = InlineStrings.String15["Fresno"]
unique(group[!, domain]) = InlineStrings.String15["Kern"]
unique(group[!, domain]) = InlineStrings.String15["Los Angeles"]
unique(group[!, domain]) = InlineStrings.String15["Mendocino"]
unique(group[!, domain]) = InlineStrings.String15["Merced"]
unique(group[!, domain]) = InlineStrings.String15["Orange"]
unique(group[!, domain]) = InlineStrings.String15["Plumas"]
unique(group[!, domain]) = InlineStrings.String15["San Diego"]
unique(group[!, domain]) = InlineStrings.String15["San Joaquin"]
unique(group[!, domain]) = InlineStrings.String15["Santa Clara"]
11×2 DataFrame
Row │ ratio cname
cname
│ Float64 String15
String15
─────┼──────────────────────
1 │ 1.09852 Alameda
2 │ 1.17779 Fresno
3 │ 1.11453 Kern
4 │ 1.06307 Los Angeles
5 │ 1.00565 Mendocino
6 │ 1.08121 Merced
7 │ 1.03628 Orange
8 │ 1.02127 Plumas
9 │ 1.06112 San Diego
10 │ 1.07331 San Joaquin
11 │ 1.05598 Santa Clara
|
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src/ratio.jl#L95
doctest failure in ~/work/Survey.jl/Survey.jl/src/ratio.jl:95-112
```jldoctest ratiolabel
julia> ratio([:api00, :api99], :cname, bclus1)
11×3 DataFrame
Row │ estimator SE cname
│ Float64 Float64 String15
─────┼─────────────────────────────────
1 │ 1.05598 NaN Santa Clara
2 │ 1.06112 NaN San Diego
3 │ 1.08121 NaN Merced
4 │ 1.06307 NaN Los Angeles
5 │ 1.03628 NaN Orange
6 │ 1.17779 NaN Fresno
7 │ 1.02127 NaN Plumas
8 │ 1.09852 NaN Alameda
9 │ 1.07331 NaN San Joaquin
10 │ 1.11453 NaN Kern
11 │ 1.00565 NaN Mendocino
```
Subexpression:
ratio([:api00, :api99], :cname, bclus1)
Evaluated output:
unique(group[!, domain]) = InlineStrings.String15["Santa Clara"]
unique(group[!, domain]) = InlineStrings.String15["San Diego"]
unique(group[!, domain]) = InlineStrings.String15["Merced"]
unique(group[!, domain]) = InlineStrings.String15["Los Angeles"]
unique(group[!, domain]) = InlineStrings.String15["Orange"]
unique(group[!, domain]) = InlineStrings.String15["Fresno"]
unique(group[!, domain]) = InlineStrings.String15["Plumas"]
unique(group[!, domain]) = InlineStrings.String15["Alameda"]
unique(group[!, domain]) = InlineStrings.String15["San Joaquin"]
unique(group[!, domain]) = InlineStrings.String15["Kern"]
unique(group[!, domain]) = InlineStrings.String15["Mendocino"]
11×3 DataFrame
Row │ estimator SE cname
│ Float64 Float64 String15
─────┼─────────────────────────────────
1 │ 1.05598 NaN Santa Clara
2 │ 1.06112 NaN San Diego
3 │ 1.08121 NaN Merced
4 │ 1.06307 NaN Los Angeles
5 │ 1.03628 NaN Orange
6 │ 1.17779 NaN Fresno
7 │ 1.02127 NaN Plumas
8 │ 1.09852 NaN Alameda
9 │ 1.07331 NaN San Joaquin
10 │ 1.11453 NaN Kern
11 │ 1.00565 NaN Mendocino
Expected output:
11×3 DataFrame
Row │ estimator SE cname
│ Float64 Float64 String15
─────┼─────────────────────────────────
1 │ 1.05598 NaN Santa Clara
2 │ 1.06112 NaN San Diego
3 │ 1.08121 NaN Merced
4 │ 1.06307 NaN Los Angeles
5 │ 1.03628 NaN Orange
6 │ 1.17779 NaN Fresno
7 │ 1.02127 NaN Plumas
8 │ 1.09852 NaN Alameda
9 │ 1.07331 NaN San Joaquin
10 │ 1.11453 NaN Kern
11 │ 1.00565 NaN Mendocino
diff =
Warning: Diff output requires color.
unique(group[!, domain]) = InlineStrings.String15["Santa Clara"]
unique(group[!, domain]) = InlineStrings.String15["San Diego"]
unique(group[!, domain]) = InlineStrings.String15["Merced"]
unique(group[!, domain]) = InlineStrings.String15["Los Angeles"]
unique(group[!, domain]) = InlineStrings.String15["Orange"]
unique(group[!, domain]) = InlineStrings.String15["Fresno"]
unique(group[!, domain]) = InlineStrings.String15["Plumas"]
unique(group[!, domain]) = InlineStrings.String15["Alameda"]
unique(group[!, domain]) = InlineStrings.String15["San Joaquin"]
unique(group[!, domain]) = InlineStrings.String15["Kern"]
unique(group[!, domain]) = InlineStrings.String15["Mendocino"]
11×3 DataFrame
Row │ estimator SE cname
cname
│ Float64 Float64 String15
String15
─────┼─────────────────────────────────
1 │ 1.05598 NaN Santa Clara
2 │ 1.06112 NaN San Diego
3 │ 1.08121 NaN Merced
4 │ 1.06307 NaN Los Angeles
5 │ 1.03628 NaN Orange
6 │ 1.17779 NaN Fresno
7 │ 1.02127 NaN Plumas
8 │ 1.09852 NaN Alameda
9 │ 1.07331 NaN San Joaquin
10 │ 1.11453 NaN Kern
11 │ 1.00565 NaN Mendocino
|
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src/total.jl#L38
doctest failure in ~/work/Survey.jl/Survey.jl/src/total.jl:38-46
```jldoctest; setup = :(using Survey; apiclus1 = load_data("apiclus1"); dclus1 = SurveyDesign(apiclus1; clusters = :dnum, weights = :pw); bclus1 = dclus1 |> bootweights;)
julia> total(:api00, bclus1)
1×2 DataFrame
Row │ total SE
│ Float64 Float64
─────┼──────────────────────
1 │ 3.98999e6 9.01611e5
```
Subexpression:
total(:api00, bclus1)
Evaluated output:
1×2 DataFrame
Row │ total SE
│ Float64 Float64
─────┼──────────────────────
1 │ 3.98999e6 9.01611e5
Expected output:
diff =
Warning: Diff output requires color.
1×2 DataFrame
Row │ total SE
│ Float64 Float64
─────┼──────────────────────
1 │ 3.98999e6 9.01611e5
|
|
src/total.jl#L99
doctest failure in ~/work/Survey.jl/Survey.jl/src/total.jl:99-116
```jldoctest totallabel; setup = :(using Survey; apiclus1 = load_data("apiclus1"); dclus1 = SurveyDesign(apiclus1; clusters = :dnum, weights = :pw); bclus1 = dclus1 |> bootweights;)
julia> total(:api00, :cname, dclus1)
11×2 DataFrame
Row │ total cname
│ Float64 String15
─────┼─────────────────────────────
1 │ 3.7362e6 Alameda
2 │ 9.58547e5 Fresno
3 │ 459473.0 Kern
4 │ 2.46465e6 Los Angeles
5 │ 1.26571e6 Mendocino
6 │ 1.0545e6 Merced
7 │ 5.7721e6 Orange
8 │ 3.2422e6 Plumas
9 │ 9.20698e6 San Diego
10 │ 1.03541e7 San Joaquin
11 │ 3.22122e6 Santa Clara
```
Subexpression:
total(:api00, :cname, dclus1)
Evaluated output:
unique(group[!, domain]) = InlineStrings.String15["Alameda"]
unique(group[!, domain]) = InlineStrings.String15["Fresno"]
unique(group[!, domain]) = InlineStrings.String15["Kern"]
unique(group[!, domain]) = InlineStrings.String15["Los Angeles"]
unique(group[!, domain]) = InlineStrings.String15["Mendocino"]
unique(group[!, domain]) = InlineStrings.String15["Merced"]
unique(group[!, domain]) = InlineStrings.String15["Orange"]
unique(group[!, domain]) = InlineStrings.String15["Plumas"]
unique(group[!, domain]) = InlineStrings.String15["San Diego"]
unique(group[!, domain]) = InlineStrings.String15["San Joaquin"]
unique(group[!, domain]) = InlineStrings.String15["Santa Clara"]
11×2 DataFrame
Row │ total cname
│ Float64 String15
─────┼─────────────────────────────
1 │ 249080.0 Alameda
2 │ 63903.1 Fresno
3 │ 30631.5 Kern
4 │ 3.2862e5 Los Angeles
5 │ 84380.6 Mendocino
6 │ 70300.2 Merced
7 │ 3.84807e5 Orange
8 │ 2.16147e5 Plumas
9 │ 1.2276e6 San Diego
10 │ 6.90276e5 San Joaquin
11 │ 6.44244e5 Santa Clara
Expected output:
11×2 DataFrame
Row │ total cname
│ Float64 String15
─────┼─────────────────────────────
1 │ 3.7362e6 Alameda
2 │ 9.58547e5 Fresno
3 │ 459473.0 Kern
4 │ 2.46465e6 Los Angeles
5 │ 1.26571e6 Mendocino
6 │ 1.0545e6 Merced
7 │ 5.7721e6 Orange
8 │ 3.2422e6 Plumas
9 │ 9.20698e6 San Diego
10 │ 1.03541e7 San Joaquin
11 │ 3.22122e6 Santa Clara
diff =
Warning: Diff output requires color.
unique(group[!, domain]) = InlineStrings.String15["Alameda"]
unique(group[!, domain]) = InlineStrings.String15["Fresno"]
unique(group[!, domain]) = InlineStrings.String15["Kern"]
unique(group[!, domain]) = InlineStrings.String15["Los Angeles"]
unique(group[!, domain]) = InlineStrings.String15["Mendocino"]
unique(group[!, domain]) = InlineStrings.String15["Merced"]
unique(group[!, domain]) = InlineStrings.String15["Orange"]
unique(group[!, domain]) = InlineStrings.String15["Plumas"]
unique(group[!, domain]) = InlineStrings.String15["San Diego"]
unique(group[!, domain]) = InlineStrings.String15["San Joaquin"]
unique(group[!, domain]) = InlineStrings.String15["Santa Clara"]
11×2 DataFrame
Row │ total cname
cname
│ Float64 String15
String15
─────┼─────────────────────────────
1 │ 3.7362e6 │ 249080.0 Alameda
2 │ 9.58547e5 │ 63903.1 Fresno
3 │ 459473.0 │ 30631.5 Kern
4 │ 2.46465e6 3.2862e5 Los Angeles
5 │ 1.26571e6 │ 84380.6 Mendocino
6 │ 1.0545e6 │ 70300.2 Merced
7 │ 5.7721e6 3.84807e5 Orange
8 │ 3.2422e6 2.16147e5 Plumas
9 │ 9.20698e6 1.2276e6 San Diego
10 │ 1.03541e7 6.90276e5 San Joaquin
11 │ 3.22122e6 6.44244e5 Santa Clara
|
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src/total.jl#L119
doctest failure in ~/work/Survey.jl/Survey.jl/src/total.jl:119-136
```jldoctest totallabel
julia> total(:api00, :cname, bclus1)
11×3 DataFrame
Row │ total SE cname
│ Float64 Float64 String15
─────┼────────────────────────────────────────
1 │ 3.22122e6 2.6143e6 Santa Clara
2 │ 9.20698e6 8.00251e6 San Diego
3 │ 1.0545e6 9.85983e5 Merced
4 │ 2.46465e6 2.15017e6 Los Angeles
5 │ 5.7721e6 5.40929e6 Orange
6 │ 9.58547e5 8.95488e5 Fresno
7 │ 3.2422e6 3.03494e6 Plumas
8 │ 3.7362e6 3.49184e6 Alameda
9 │ 1.03541e7 9.69862e6 San Joaquin
10 │ 459473.0 4.30027e5 Kern
11 │ 1.26571e6 1.18696e6 Mendocino
```
Subexpression:
total(:api00, :cname, bclus1)
Evaluated output:
unique(group[!, domain]) = InlineStrings.String15["Santa Clara"]
unique(group[!, domain]) = InlineStrings.String15["San Diego"]
unique(group[!, domain]) = InlineStrings.String15["Merced"]
unique(group[!, domain]) = InlineStrings.String15["Los Angeles"]
unique(group[!, domain]) = InlineStrings.String15["Orange"]
unique(group[!, domain]) = InlineStrings.String15["Fresno"]
unique(group[!, domain]) = InlineStrings.String15["Plumas"]
unique(group[!, domain]) = InlineStrings.String15["Alameda"]
unique(group[!, domain]) = InlineStrings.String15["San Joaquin"]
unique(group[!, domain]) = InlineStrings.String15["Kern"]
unique(group[!, domain]) = InlineStrings.String15["Mendocino"]
11×3 DataFrame
Row │ total SE cname
│ Float64 Float64 String15
─────┼────────────────────────────────────────────
1 │ 6.44244e5 4.2273e5 Santa Clara
2 │ 1.2276e6 8.62727e5 San Diego
3 │ 70300.2 71336.3 Merced
4 │ 3.2862e5 2.93936e5 Los Angeles
5 │ 3.84807e5 3.88014e5 Orange
6 │ 63903.1 64781.7 Fresno
7 │ 2.16147e5 2.12089e5 Plumas
8 │ 249080.0 2.49228e5 Alameda
9 │ 6.90276e5 6.81604e5 San Joaquin
10 │ 30631.5 30870.3 Kern
11 │ 84380.6 80215.9 Mendocino
Expected output:
11×3 DataFrame
Row │ total SE cname
│ Float64 Float64 String15
─────┼────────────────────────────────────────
1 │ 3.22122e6 2.6143e6 Santa Clara
2 │ 9.20698e6 8.00251e6 San Diego
3 │ 1.0545e6 9.85983e5 Merced
4 │ 2.46465e6 2.15017e6 Los Angeles
5 │ 5.7721e6 5.40929e6 Orange
6 │ 9.58547e5 8.95488e5 Fresno
7 │ 3.2422e6 3.03494e6 Plumas
8 │ 3.7362e6 3.49184e6 Alameda
9 │ 1.03541e7 9.69862e6 San Joaquin
10 │ 459473.0 4.30027e5 Kern
11 │ 1.26571e6 1.18696e6 Mendocino
diff =
Warning: Diff output requires color.
unique(group[!, domain]) = InlineStrings.String15["Santa Clara"]
unique(group[!, domain]) = InlineStrings.String15["San Diego"]
unique(group[!, domain]) = InlineStrings.String15["Merced"]
unique(group[!, domain]) = InlineStrings.String15["Los Angeles"]
unique(group[!, domain]) = InlineStrings.String15["Orange"]
unique(group[!, domain]) = InlineStrings.String15["Fresno"]
unique(group[!, domain]) = InlineStrings.String15["Plumas"]
unique(group[!, domain]) = InlineStrings.String15["Alameda"]
unique(group[!, domain]) = InlineStrings.String15["San Joaquin"]
unique(group[!, domain]) = InlineStrings.String15["Kern"]
unique(group[!, domain]) = InlineStrings.String15["Mendocino"]
11×3 DataFrame
Row │ total SE cname
SE cname
│ Float64 Float64 String15
─────┼────────────────────────────────────────
Float64 String15
─────┼────────────────────────────────────────────
1 │ 3.22122e6 2.6143e6 6.44244e5 4.2273e5 Santa Clara
2 │ 9.20698e6 8.00251e6 1.2276e6 8.62727e5 San Diego
3 │ 1.0545e6 9.85983e5 │ 70300.2
|
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src/bootstrap.jl#L81
doctest failure in ~/work/Survey.jl/Survey.jl/src/bootstrap.jl:81-91
```jldoctest; setup = :(using Survey, StatsBase, DataFrames; apiclus1 = load_data("apiclus1"); dclus1 = SurveyDesign(apiclus1; clusters = :dnum, weights = :pw); bclus1 = dclus1 |> bootweights;)
julia> mean(df::DataFrame, column, weights) = StatsBase.mean(df[!, column], StatsBase.weights(df[!, weights]));
julia> variance(:api00, mean, bclus1)
1×2 DataFrame
Row │ estimator SE
│ Float64 Float64
─────┼────────────────────
1 │ 644.169 23.4107
```
Subexpression:
variance(:api00, mean, bclus1)
Evaluated output:
1×2 DataFrame
Row │ estimator SE
│ Float64 Float64
─────┼────────────────────
1 │ 644.169 23.4107
Expected output:
diff =
Warning: Diff output requires color.
1×2 DataFrame
Row │ estimator SE
│ Float64 Float64
─────┼────────────────────
1 │ 644.169 23.4107
|
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src/jackknife.jl#L97
doctest failure in ~/work/Survey.jl/Survey.jl/src/jackknife.jl:97-107
```jldoctest; setup = :(using Survey, StatsBase, DataFrames; apistrat = load_data("apistrat"); dstrat = SurveyDesign(apistrat; strata=:stype, weights=:pw); rstrat = jackknifeweights(dstrat);)
julia> mean(df::DataFrame, column, weights) = StatsBase.mean(df[!, column], StatsBase.weights(df[!, weights]));
julia> variance(:api00, mean, rstrat)
1×2 DataFrame
Row │ estimator SE
│ Float64 Float64
─────┼────────────────────
1 │ 662.287 9.53613
```
Subexpression:
variance(:api00, mean, rstrat)
Evaluated output:
1×2 DataFrame
Row │ estimator SE
│ Float64 Float64
─────┼────────────────────
1 │ 662.287 9.53613
Expected output:
diff =
Warning: Diff output requires color.
1×2 DataFrame
Row │ estimator SE
│ Float64 Float64
─────┼────────────────────
1 │ 662.287 9.53613
|
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src/mean.jl#L47
doctest failure in ~/work/Survey.jl/Survey.jl/src/mean.jl:47-55
```jldoctest; setup = :(using Survey, StatsBase; apiclus1 = load_data("apiclus1"); dclus1 = SurveyDesign(apiclus1; clusters = :dnum, weights = :pw); bclus1 = dclus1 |> bootweights;)
julia> mean(:api00, bclus1)
1×2 DataFrame
Row │ mean SE
│ Float64 Float64
─────┼──────────────────
1 │ 644.169 23.4107
```
Subexpression:
mean(:api00, bclus1)
Evaluated output:
1×2 DataFrame
Row │ mean SE
│ Float64 Float64
─────┼──────────────────
1 │ 644.169 23.4107
Expected output:
diff =
Warning: Diff output requires color.
1×2 DataFrame
Row │ mean SE
│ Float64 Float64
─────┼──────────────────
1 │ 644.169 23.4107
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