use _init_parmas for MCMCThreads and MCMCDistributed too

src/sample.jl

@@ -410,6 +410,9 @@ function mcmcsample(
         @warn "Number of chains ($nchains) is greater than number of samples per chain ($N)"
     end
 
+    # Ensure that initial parameters are `nothing` or indexable
+    _init_params = _first_or_nothing(init_params, nchains)
+
     # Create a seed for each chain using the provided random number generator.
     seeds = rand(rng, UInt, nchains)
 
@@ -466,10 +469,10 @@ function mcmcsample(
                         # Return the new chain.
                         return chain
                     end
-                    chains = if init_params === nothing
+                    chains = if _init_params === nothing
                         Distributed.pmap(sample_chain, pool, seeds)
                     else
-                        Distributed.pmap(sample_chain, pool, seeds, init_params)
+                        Distributed.pmap(sample_chain, pool, seeds, _init_params)
                     end
                 finally
                     # Stop updating the progress bar.
@@ -499,6 +502,9 @@ function mcmcsample(
         @warn "Number of chains ($nchains) is greater than number of samples per chain ($N)"
     end
 
+    # Ensure that initial parameters are `nothing` or indexable
+    _init_params = _first_or_nothing(init_params, nchains)
+
     # Create a seed for each chain using the provided random number generator.
     seeds = rand(rng, UInt, nchains)
 
@@ -519,10 +525,10 @@ function mcmcsample(
         )
     end
 
-    chains = if init_params === nothing
+    chains = if _init_params === nothing
         map(sample_chain, 1:nchains, seeds)
     else
-        map(sample_chain, 1:nchains, seeds, init_params)
+        map(sample_chain, 1:nchains, seeds, _init_params)
     end
 
     # Concatenate the chains together.