add cooksdistance delegation for LinearModel (#221)

* add cooksdistance delegation for LinearModel

add cooksdistance delegation for LinearModel in GLM.jl

* Require StatsBase 0.33.5.

* bump patch version

Co-authored-by: Milan Bouchet-Valat <nalimilan@club.fr>
Co-authored-by: Dave Kleinschmidt <dave.f.kleinschmidt@gmail.com>

Author: 3 people

Project.toml

@@ -1,6 +1,6 @@
 name = "StatsModels"
 uuid = "3eaba693-59b7-5ba5-a881-562e759f1c8d"
-version = "0.6.21"
+version = "0.6.22"
 
 [deps]
 DataAPI = "9a962f9c-6df0-11e9-0e5d-c546b8b5ee8a"
@@ -19,7 +19,7 @@ DataAPI = "1.1"
 DataFrames = "0.21"
 DataStructures = "0.17.0, 0.18"
 ShiftedArrays = "1.0.0"
-StatsBase = "0.22, 0.23, 0.24, 0.25, 0.26, 0.27, 0.28, 0.29, 0.30, 0.31, 0.32, 0.33"
+StatsBase = "0.33.5"
 StatsFuns = "0.9"
 Tables = "0.2, 1"
 julia = "1"

src/statsmodel.jl

@@ -122,7 +122,8 @@ const TableModels = Union{TableStatisticalModel, TableRegressionModel}
                              StatsBase.stderror, StatsBase.vcov]
 @delegate TableRegressionModel.model [StatsBase.modelmatrix,
                                       StatsBase.residuals, StatsBase.response,
-                                      StatsBase.predict, StatsBase.predict!]
+                                      StatsBase.predict, StatsBase.predict!, 
+                                      StatsBase.cooksdistance]
 StatsBase.predict(m::TableRegressionModel, new_x::AbstractMatrix; kwargs...) =
     predict(m.model, new_x; kwargs...)
 # Need to define these manually because of ambiguity using @delegate