Remove StatisticalRethinking as a dependency.

Author: goedman

Project.toml

@@ -4,19 +4,24 @@ authors = ["@alvaro1101, Rob J Goedman <goedman@icloud.com"]
 version = "0.1.0"
 
 [deps]
+CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
+DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
+Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 JSON = "682c06a0-de6a-54ab-a142-c8b1cf79cde6"
 Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
+Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 StanSample = "c1514b29-d3a0-5178-b312-660c88baa699"
-StatisticalRethinking = "2d09df54-9d0f-5258-8220-54c2a3d4fbee"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 StatsFuns = "4c63d2b9-4356-54db-8cca-17b64c39e42c"
 StatsPlots = "f3b207a7-027a-5e70-b257-86293d7955fd"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [compat]
+CSV = "0.8"
+DataFrames = "0.22"
+Distributions = "0.24"
 JSON = "0.21"
 StanSample = "3.0"
-StatisticalRethinking = "3.2"
 StatsFuns = "0.9"
 StatsPlots = "0.14"
 julia = "1"

examples/arsenic/compare.png

@@ -1,3 +1,5 @@
+using Random
+
 # CVIT - Create itr and itst indeces for k-fold-cv
 #
 #    Description

examples/arsenic/cvit.jl

@@ -1,7 +1,6 @@
-using StatisticalRethinking
-using JSON
-using StanSample
 using ParetoSmoothedImportanceSampling
+using StanSample, StatsFuns, StatsPlots
+using JSON
 using Printf
 
 ProjDir = @__DIR__

examples/arsenic/demo_wells.jl

@@ -1,5 +1,5 @@
-using StatisticalRethinking, StanSample
-using ParetoSmoothedImportanceSampling, RDatasets
+using ParetoSmoothedImportanceSampling, StanSample
+using StatsFuns, RDatasets
 
 df = RDatasets.dataset("datasets", "cars")
 
@@ -36,8 +36,7 @@ data = (N = size(df, 1), speed = df.Speed, dist = df.Dist)
 rc = stan_sample(cars_stan_model; data)
 
 if success(rc)
-    cars_df = read_samples(cars_stan_model; output_format=:dataframe)
-    precis(cars_df[:, [:a, :b, :sigma]])
+    stan_summary(cars_stan_model, true)
     nt_cars = read_samples(cars_stan_model);
 end
 

examples/cars_waic/cars.jl

@@ -1,5 +1,5 @@
-using StatisticalRethinking, StanSample
-using Printf, ParetoSmoothedImportanceSampling
+using ParetoSmoothedImportanceSampling, StanSample
+using CSV, Printf, StatsPlots
 
 ProjDir = @__DIR__
 
@@ -47,8 +47,7 @@ sm1 = SampleModel("roaches1", roaches1_stan; tmpdir)
 rc1 = stan_sample(sm1; data)
 
 if success(rc1)
-  roaches1_df = read_samples(sm1; output_format=:dataframe)
-  precis(roaches1_df[:, [Symbol("beta.$i") for i in 1:data.K]])
+  stan_summary(sm1, true)
   nt1 = read_samples(sm1)
 
   # Compute LOO and standard error
@@ -129,8 +128,7 @@ sm2 = SampleModel("roaches2", roaches2_stan; tmpdir)
 rc2 = stan_sample(sm2; data)
 
 if success(rc2)
-  roaches2_df = read_samples(sm2; output_format=:dataframe)
-  precis(roaches2_df[:, [Symbol("beta.$i") for i in 1:data.K]])
+  read_summary(sm2, true)
   nt2 = read_samples(sm2)
 
   # Compute LOO and standard error
@@ -141,14 +139,8 @@ if success(rc2)
   @printf(">> elpd_loo = %.1f, SE(elpd_loo) = %.1f\n", elpd_loo2, se_elpd_loo2)
 
   # Check the shape parameter k of the generalized Pareto distribution
-  if all(pk2 .< 0.5)
-      println("All Pareto k estimates OK (k < 0.5).")
-  else
-    pk_good = sum(pk2 .<= 0.5)
-    pk_ok = length(pk2[pk2 .<= 0.7]) - pk_good
-    pk_bad = length(pk2[pk2 .<= 1]) - pk_good - pk_ok
-    println((good=pk_good, ok=pk_ok, bad=pk_bad, very_bad=sum(pk2 .> 1)))
-  end
+  pk_qualify(pk2) |> display
+  
 end
 
 begin

examples/roaches/diag_plot_1.png

@@ -9,9 +9,8 @@ using Pkg, DrWatson, ParetoSmoothedImportanceSampling
 
 # ╔═╡ d4f7a39c-5ebb-11eb-0a37-4b8499832108
 begin
-	using StatisticalRethinking
+	using StanSample, StatsFuns, StatsPlots
 	using JSON
-	using StanSample
 
 	ProjDir = joinpath(psis_path, "..", "examples", "arsenic")
 	include(joinpath(ProjDir, "cvit.jl"))

examples/roaches/diag_plot_2.png

@@ -9,9 +9,8 @@ using Pkg, DrWatson, ParetoSmoothedImportanceSampling
 
 # ╔═╡ 20d3ad36-6008-11eb-2f2a-d379b234b0e9
 begin
-	using StatisticalRethinking
-	using StanSample
-	using RDatasets
+	using StanSample, StatsFuns, StatsPlots
+	using DataFrames, RDatasets
 end;
 
 # ╔═╡ af6b0b20-6008-11eb-2fa1-2f61145ab7db
@@ -67,7 +66,8 @@ begin
 
 	if success(rc)
 		cars_df = read_samples(cars_stan_model; output_format=:dataframe)
-		PRECIS(cars_df[:, [:a, :b, :sigma]])
+		isdefined(Main, :StatisticalRethinking) && 
+            PRECIS(cars_df[:, [:a, :b, :sigma]])
 	end
 end