version bump fixed

JuliaStats · Jul 30, 2019 · 4d71fc7 · 4d71fc7
2 parents 5bd3173 + b9454f9
commit 4d71fc7
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diff --git a/.travis.yml b/.travis.yml
@@ -3,8 +3,8 @@ os:
   - linux
   - osx
 julia:
-  - 0.7
   - 1.0
+  - 1.2
   - nightly
 notifications:
   email: false
@@ -17,4 +17,14 @@ git:
 #  - julia -e 'Pkg.clone(pwd()); Pkg.build("StatsBase"); Pkg.test("StatsBase"; coverage=true)'
 after_success:
   - julia -e 'using Pkg; Pkg.add("Coverage"); using Coverage; Coveralls.submit(process_folder()); Codecov.submit(process_folder())';
-  - julia -e 'using Pkg; Pkg.add("Documenter"); include(joinpath("docs", "make.jl"))'
+jobs:
+  include:
+    - stage: "Documentation"
+      julia: 1.0
+      os: linux
+      script:
+        - julia --project=docs/ -e 'using Pkg; Pkg.develop(PackageSpec(path=pwd()));
+                                    Pkg.instantiate()'
+        - julia --project=docs/ docs/make.jl
+      after_success: skip
+
diff --git a/Project.toml b/Project.toml
@@ -4,18 +4,23 @@ authors = ["JuliaStats"]
 version = "0.32.0"
 
 [deps]
+DataAPI = "9a962f9c-6df0-11e9-0e5d-c546b8b5ee8a"
 DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
+LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 Missings = "e1d29d7a-bbdc-5cf2-9ac0-f12de2c33e28"
 Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
+Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 SortingAlgorithms = "a2af1166-a08f-5f64-846c-94a0d3cef48c"
+SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 
 [extras]
+Dates = "ade2ca70-3891-5945-98fb-dc099432e06a"
 DelimitedFiles = "8bb1440f-4735-579b-a4ab-409b98df4dab"
-LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
-Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
-SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["DelimitedFiles", "LinearAlgebra", "Random", "SparseArrays", "Test"]
+test = ["Dates", "DelimitedFiles", "Test"]
+
+[compat]
+julia = "1"
diff --git a/REQUIRE b/REQUIRE
diff --git a/appveyor.yml b/appveyor.yml
@@ -1,7 +1,7 @@
 environment:
   matrix:
-  - julia_version: 0.7
   - julia_version: 1.0
+  - julia_version: 1.2
   - julia_version: nightly
 
 platform:

diff --git a/docs/Project.toml b/docs/Project.toml
@@ -0,0 +1,5 @@
+[deps]
+Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
+
+[compat]
+Documenter = "~0.22"
diff --git a/docs/make.jl b/docs/make.jl
@@ -1,7 +1,11 @@
 using Documenter, StatsBase, Statistics, Random
 
+# Workaround for JuliaLang/julia/pull/28625
+if Base.HOME_PROJECT[] !== nothing
+    Base.HOME_PROJECT[] = abspath(Base.HOME_PROJECT[])
+end
+
 makedocs(
-    format = :html,
     sitename = "StatsBase.jl",
     modules = [StatsBase],
     pages = ["index.md",
@@ -23,9 +27,5 @@ makedocs(
 )
 
 deploydocs(
-    repo = "github.com/JuliaStats/StatsBase.jl.git",
-    target = "build",
-    julia  = "1.0",
-    deps   = nothing,
-    make   = nothing
-)
+    repo = "github.com/JuliaStats/StatsBase.jl.git"
+)
diff --git a/docs/src/cov.md b/docs/src/cov.md
@@ -5,8 +5,13 @@ This package implements functions for computing scatter matrix, as well as weigh
 ```@docs
 scattermat
 cov
+cov(::CovarianceEstimator, ::AbstractVector)
+cov(::CovarianceEstimator, ::AbstractVector, ::AbstractVector)
+cov(::CovarianceEstimator, ::AbstractMatrix)
 cor
 mean_and_cov
 cov2cor
 cor2cov
+CovarianceEstimator
+SimpleCovariance
 ```
diff --git a/docs/src/weights.md b/docs/src/weights.md
@@ -50,6 +50,71 @@ w = Weights([1., 2., 3.])
 w = weights([1., 2., 3.])
 ```
 
+### Exponential weights: `eweights`
+
+Exponential weights are a common form of temporal weights which assign exponentially decreasing
+weights to past observations.
+
+If `t` is a vector of temporal indices then for each index `i` we compute the weight as:
+
+``λ (1 - λ)^{1 - i}``
+
+``λ`` is a smoothing factor or rate parameter such that ``0 < λ ≤ 1``.
+As this value approaches 0, the resulting weights will be almost equal,
+while values closer to 1 will put greater weight on the tail elements of the vector.
+
+For example, the following call generates exponential weights for ten observations with ``λ = 0.3``.
+```julia-repl
+julia> eweights(1:10, 0.3)
+10-element Weights{Float64,Float64,Array{Float64,1}}:
+ 0.3
+ 0.42857142857142855
+ 0.6122448979591837
+ 0.8746355685131197
+ 1.249479383590171
+ 1.7849705479859588
+ 2.549957925694227
+ 3.642797036706039
+ 5.203995766722913
+ 7.434279666747019
+```
+
+Simply passing the number of observations `n` is equivalent to passing in `1:n`.
+
+```julia-repl
+julia> eweights(10, 0.3)
+10-element Weights{Float64,Float64,Array{Float64,1}}:
+ 0.3
+ 0.42857142857142855
+ 0.6122448979591837
+ 0.8746355685131197
+ 1.249479383590171
+ 1.7849705479859588
+ 2.549957925694227
+ 3.642797036706039
+ 5.203995766722913
+ 7.434279666747019
+```
+
+Finally, you can construct exponential weights from an arbitrary subset of timestamps within a larger range.
+
+```julia-repl
+julia> t
+2019-01-01T01:00:00:2 hours:2019-01-01T05:00:00
+
+julia> r
+2019-01-01T01:00:00:1 hour:2019-01-02T01:00:00
+
+julia> eweights(t, r, 0.3)
+3-element Weights{Float64,Float64,Array{Float64,1}}:
+ 0.3
+ 0.6122448979591837
+ 1.249479383590171
+```
+
+NOTE: This is equivalent to `eweights(something.(indexin(t, r)), 0.3)`, which is saying that for each value in `t` return the corresponding index for that value in `r`.
+Since `indexin` returns `nothing` if there is no corresponding value from `t` in `r` we use `something` to eliminate that possibility.
+
 ## Methods
 
 `AbstractWeights` implements the following methods:
@@ -70,5 +135,6 @@ Weights
 aweights
 fweights
 pweights
+eweights
 weights
-```
+```
diff --git a/src/StatsBase.jl b/src/StatsBase.jl
@@ -1,27 +1,28 @@
-__precompile__()
-
 module StatsBase
-    import Base: length, isempty, eltype, values, sum, show, maximum, minimum, extrema
-    import Base.Cartesian: @nloops, @nref, @nextract
-    using Base: @irrational, @propagate_inbounds
-    import DataStructures: heapify!, heappop!, percolate_down!
-    using SortingAlgorithms
-    using Missings
-
-    using Statistics
-    using LinearAlgebra
-    using Random
-    using Printf
-    using SparseArrays
-    import Random: rand, rand!
-    import LinearAlgebra: BlasReal, BlasFloat
-    import Statistics: mean, mean!, var, varm, varm!, std, stdm, cov, covm,
-                       cor, corm, cov2cor!, unscaled_covzm, quantile, sqrt!,
-                       median, middle
+
+import Base: length, isempty, eltype, values, sum, show, maximum, minimum, extrema
+import Base.Cartesian: @nloops, @nref, @nextract
+using Base: @irrational, @propagate_inbounds
+using DataAPI
+import DataAPI: describe
+import DataStructures: heapify!, heappop!, percolate_down!
+using SortingAlgorithms
+using Missings
+
+using Statistics
+using LinearAlgebra
+using Random
+using Printf
+using SparseArrays
+import Random: rand, rand!
+import LinearAlgebra: BlasReal, BlasFloat
+import Statistics: mean, mean!, var, varm, varm!, std, stdm, cov, covm,
+                   cor, corm, cov2cor!, unscaled_covzm, quantile, sqrt!,
+                   median, middle
 
     ## tackle compatibility issues
 
-    export
+export
 
     ## weights
     AbstractWeights,    # abstract type to represent any weight vector
@@ -33,6 +34,7 @@ module StatsBase
     aweights,           # construct an AnalyticWeights vector
     fweights,           # construct a FrequencyWeights vector
     pweights,           # construct a ProbabilityWeights vector
+    eweights,           # construct an exponential Weights vector
     wsum,               # weighted sum with vector as second argument
     wsum!,              # weighted sum across dimensions with provided storage
     wmean,              # weighted mean
@@ -97,6 +99,8 @@ module StatsBase
     scattermat,     # scatter matrix (i.e. unnormalized covariance)
     cov2cor,        # converts a covariance matrix to a correlation matrix
     cor2cov,        # converts a correlation matrix to a covariance matrix
+    CovarianceEstimator, # abstract type for covariance estimators
+    SimpleCovariance,    # simple covariance estimator
 
     ## counts
     addcounts!,     # add counts to an accumulating array or map
@@ -207,30 +211,30 @@ module StatsBase
     ZScoreTransform,       # the type to represent a z-score data transformation
     UnitRangeTransform     # the type to represent a 0-1 data transformation
 
-    # source files
-
-    include("common.jl")
-    include("weights.jl")
-    include("moments.jl")
-    include("scalarstats.jl")
-    include("robust.jl")
-    include("deviation.jl")
-    include("cov.jl")
-    include("counts.jl")
-    include("ranking.jl")
-    include("toeplitzsolvers.jl")
-    include("rankcorr.jl")
-    include("signalcorr.jl")
-    include("partialcor.jl")
-    include("empirical.jl")
-    include("hist.jl")
-    include("misc.jl")
-
-    include("sampling.jl")
-    include("statmodels.jl")
-
-    include("transformations.jl")
-
-    include("deprecates.jl")
+# source files
+
+include("common.jl")
+include("weights.jl")
+include("moments.jl")
+include("scalarstats.jl")
+include("robust.jl")
+include("deviation.jl")
+include("cov.jl")
+include("counts.jl")
+include("ranking.jl")
+include("toeplitzsolvers.jl")
+include("rankcorr.jl")
+include("signalcorr.jl")
+include("partialcor.jl")
+include("empirical.jl")
+include("hist.jl")
+include("misc.jl")
+
+include("sampling.jl")
+include("statmodels.jl")
+
+include("transformations.jl")
+
+include("deprecates.jl")
 
 end # module