Rel 1.3.1 - StatsFuns 1.0

Project.toml

@@ -1,7 +1,7 @@
 name = "ParetoSmoothedImportanceSampling"
 uuid = "98f080ec-61e2-11eb-1c7b-31ea1097256f"
 authors = ["@alvaro1101, Rob J Goedman <[email protected]>"]
-version = "1.3.1"
+version = "1.3.2"
 
 [deps]
 CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
@@ -22,6 +22,6 @@ DataFrames = "1.3"
 Distributions = "0.25"
 JSON = "0.21"
 StanSample = "6"
-StatsFuns = "0.9"
+StatsFuns = "0.9, 1.0"
 StatsPlots = "0.14"
 julia = "1"

test/test_demo_wells.jl

@@ -21,7 +21,7 @@ sm1 = SampleModel("arsenic_logistic", model_str)
 
 data1 = (p = m, N = n, y = Int.(y), x = x)
 # Fit the model in Stan
-rc1 = stan_sample(sm1, false; data=data1)
+rc1 = stan_sample(sm1; use_json=false, data=data1)
 if success(rc1)
     nt1 = read_samples(sm1, :namedtuple)
 
@@ -50,7 +50,7 @@ x2 = Float64[log.(data["arsenic"])  data["dist"]]
 # Model
 data2 = (p = m, N = n, y = Int.(y), x = x2)
 # Fit the model in Stan
-rc2 = stan_sample(sm1, false; data=data2)
+rc2 = stan_sample(sm1; use_json=false, data=data2)
 
 if success(rc2)
     nt2 = read_samples(sm1, :namedtuple)
@@ -94,7 +94,7 @@ for cvi in 1:3
         xt = x[cvitst[cvi],:], yt = Int.(y[cvitst[cvi]]))
 
     # Fit the model in Stan
-    rc3 = stan_sample(sm3, false; data=standatacv)
+    rc3 = stan_sample(sm3; use_json=false, data=standatacv)
     if success(rc3)
         nt3 = read_samples(sm3, :namedtuple)
         # Compute LOO and standard error