begin supporting public keyword

NEWS.md

@@ -1,3 +1,8 @@
+MixedModels v4.25.2 Release Notes
+==============================
+- Use `public` keyword so that users don't see unnecessary docstring warnings on 1.11+. [#776]
+- Fix accidental export of `dataset` and `datasets` and make them `public` instead. [#776]
+
 MixedModels v4.25.1 Release Notes
 ==============================
 - Use more sophisticated checks on property names in `restoreoptsum` to allow for optsums saved by pre-v4.25 versions to be used with this version and later. [#775] 
@@ -543,3 +548,4 @@ Package dependencies
 [#772]: https://github.com/JuliaStats/MixedModels.jl/issues/772
 [#773]: https://github.com/JuliaStats/MixedModels.jl/issues/773
 [#775]: https://github.com/JuliaStats/MixedModels.jl/issues/775
+[#776]: https://github.com/JuliaStats/MixedModels.jl/issues/776

Project.toml

@@ -1,11 +1,12 @@
 name = "MixedModels"
 uuid = "ff71e718-51f3-5ec2-a782-8ffcbfa3c316"
 author = ["Phillip Alday <me@phillipalday.com>", "Douglas Bates <dmbates@gmail.com>", "Jose Bayoan Santiago Calderon <jbs3hp@virginia.edu>"]
-version = "4.25.1"
+version = "4.25.2"
 
 [deps]
 Arrow = "69666777-d1a9-59fb-9406-91d4454c9d45"
 BSplineKit = "093aae92-e908-43d7-9660-e50ee39d5a0a"
+Compat = "34da2185-b29b-5c13-b0c7-acf172513d20"
 DataAPI = "9a962f9c-6df0-11e9-0e5d-c546b8b5ee8a"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 GLM = "38e38edf-8417-5370-95a0-9cbb8c7f171a"
@@ -33,6 +34,7 @@ TypedTables = "9d95f2ec-7b3d-5a63-8d20-e2491e220bb9"
 Aqua = "0.8"
 Arrow = "1, 2"
 BSplineKit = "0.14, 0.15, 0.16, 0.17"
+Compat = "4.10"
 DataAPI = "1"
 DataFrames = "1"
 Distributions = "0.21, 0.22, 0.23, 0.24, 0.25"

src/MixedModels.jl

@@ -4,6 +4,7 @@ using Arrow: Arrow
 using Base: Ryu, require_one_based_indexing
 using BSplineKit: BSplineKit, BSplineOrder, Natural, Derivative, SplineInterpolation
 using BSplineKit: interpolate
+using Compat: @compat
 using DataAPI: DataAPI, levels, refpool, refarray, refvalue
 using Distributions: Distributions, Bernoulli, Binomial, Chisq, Distribution, Gamma
 using Distributions: InverseGaussian, Normal, Poisson, ccdf
@@ -89,8 +90,6 @@ export @formula,
     condVar,
     condVartables,
     confint,
-    dataset,
-    datasets,
     deviance,
     dispersion,
     dispersion_parameter,
@@ -160,6 +159,8 @@ export @formula,
 # TODO: move this to the correct spot in list once we've decided on name
 export savereplicates, restorereplicates
 
+@compat public rePCA, PCA, dataset, datasets
+
 """
     MixedModel
 
@@ -209,8 +210,8 @@ include("profile/profile.jl")
 @setup_workload begin
     # Putting some things in `setup` can reduce the size of the
     # precompile file and potentially make loading faster.
-    sleepstudy = MixedModels.dataset(:sleepstudy)
-    contra = MixedModels.dataset(:contra)
+    sleepstudy = dataset(:sleepstudy)
+    contra = dataset(:contra)
     progress = false
     @compile_workload begin
         # all calls in this block will be precompiled, regardless of whether

test/pls.jl

@@ -628,7 +628,7 @@ end
 """
         )
         @test_throws(ArgumentError("initial or final parameters in io do not satisfy lowerbd"),
-                     restoreoptsum!(m, seekstart(iob)))
+                     @suppress restoreoptsum!(m, seekstart(iob)))
 
         # make sure new fields are correctly restored
         mktemp() do path, io
@@ -638,15 +638,15 @@ end
             saveoptsum(io, m)
             m.optsum.xtol_zero_abs = 1.0
             m.optsum.ftol_zero_abs = 1.0
-            restoreoptsum!(m, seekstart(io))
+            @suppress restoreoptsum!(m, seekstart(io))
             @test m.optsum.xtol_zero_abs == 0.5
             @test m.optsum.ftol_zero_abs == 0.5
         end
 
     end
 
     @testset "profile" begin
-        pr = profile(last(models(:sleepstudy)))
+        pr = @suppress profile(last(models(:sleepstudy)))
         tbl = pr.tbl
         @test length(tbl) >= 122
         ci = confint(pr)

test/predict.jl

@@ -143,7 +143,7 @@ end
         slp1 = subset(slp, :days => ByRow(>(0)))
         # this model probably doesn't make much sense, but it has two
         # variables on the left hand side in a FunctionTerm
-        m = fit(MixedModel, @formula(reaction / days ~ 1 + (1|subj)), slp1)
+        m = @suppress fit(MixedModel, @formula(reaction / days ~ 1 + (1|subj)), slp1)
         # make sure that we're getting the transformation
         @test response(m) ≈ slp1.reaction ./ slp1.days
         @test_throws ArgumentError predict(m, slp[:, Not(:reaction)])
@@ -154,7 +154,7 @@ end
         @test predict(m, slp1) ≈ fitted(m)
 
 
-        m = fit(MixedModel, @formula(log10(reaction) ~ 1 + days + (1|subj)), slp1)
+        m = @suppress fit(MixedModel, @formula(log10(reaction) ~ 1 + days + (1|subj)), slp1)
         # make sure that we're getting the transformation
         @test response(m) ≈ log10.(slp1.reaction)
         @test_throws ArgumentError predict(m, slp[:, Not(:reaction)])