Rename :confint to :confidence

JuliaStats · Nov 10, 2018 · c2a5bd2 · c2a5bd2
1 parent 2e1fef4
commit c2a5bd2
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Showing 3 changed files with 10 additions and 6 deletions.
diff --git a/docs/src/index.md b/docs/src/index.md
@@ -83,7 +83,7 @@ julia> predict(ols)
 
 julia> newX = DataFrame(X=[2,3,4]);
 
-julia> predict(ols, newX, interval=:confint)
+julia> predict(ols, newX, interval=:confidence)
  3×3 Array{Float64,2}:
   4.33333  1.33845   7.32821
   6.83333  2.09801  11.5687

diff --git a/src/lm.jl b/src/lm.jl
@@ -194,16 +194,20 @@ If `interval` is `nothing` (the default), return a vector with the predicted val
 for model `mm` and new data `newx`.
 Otherwise, return a 3-column matrix with the prediction and
 the lower and upper confidence bounds for a given `level` (0.95 equates alpha = 0.05).
-Valid values of `interval` are `:confint` delimiting the  uncertainty of the
-predicted relationship, and `:predint` delimiting estimated bounds for new data points.
+Valid values of `interval` are `:confidence` delimiting the  uncertainty of the
+predicted relationship, and `:prediction` delimiting estimated bounds for new data points.
 """
 function predict(mm::LinearModel, newx::AbstractMatrix;
                  interval::Union{Symbol,Nothing}=nothing, level::Real = 0.95)
     retmean = newx * coef(mm)
+    if interval === :confint
+        Base.depwarn("interval=:confint is deprecated in favor of interval=:confidence")
+        interval = :confidence
+    end
     if interval === nothing
         return retmean
-    elseif interval !== :confint
-        error("only :confint is currently implemented") #:predint will be implemented
+    elseif interval !== :confidence
+        error("only interval=:confidence is currently implemented") #:predint will be implemented
     end
     length(mm.rr.wts) == 0 || error("prediction with confidence intervals not yet implemented for weighted regression")
 

diff --git a/test/runtests.jl b/test/runtests.jl
@@ -452,7 +452,7 @@ end
     Ylm = X * [0.8, 1.6] + 0.8randn(10)
     mm = fit(LinearModel, X, Ylm)
     pred1 = predict(mm, newX)
-    pred2 = predict(mm, newX, interval=:confint)
+    pred2 = predict(mm, newX, interval=:confidence)
 
     @test pred1 == pred2[:, 1] ≈
         [1.6488076594462182, 0.4706674451801356, 2.5010808086024423,