diff --git a/Manifest.toml b/Manifest.toml
new file mode 100644
index 0000000..b262b8f
--- /dev/null
+++ b/Manifest.toml
@@ -0,0 +1,358 @@
+[[Arpack]]
+deps = ["BinaryProvider", "Libdl", "LinearAlgebra", "Random", "SparseArrays", "Test"]
+git-tree-sha1 = "5b046410fb617d9cf2f8bc0edd5da05a2e5a2ad4"
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+version = "0.2.3"
+
+[[Base64]]
+uuid = "2a0f44e3-6c83-55bd-87e4-b1978d98bd5f"
+
+[[BinDeps]]
+deps = ["Compat", "Libdl", "SHA", "URIParser"]
+git-tree-sha1 = "12093ca6cdd0ee547c39b1870e0c9c3f154d9ca9"
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+[[BinaryProvider]]
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+[[Compat]]
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+[[Distributions]]
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+[[Future]]
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+[[GLM]]
+deps = ["Distributions", "LinearAlgebra", "Pkg", "Printf", "Random", "Reexport", "SparseArrays", "SpecialFunctions", "Statistics", "StatsBase", "StatsFuns", "StatsModels"]
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+[[InteractiveUtils]]
+deps = ["LinearAlgebra", "Markdown"]
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+[[JLD2]]
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+
+[[JSON]]
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+[[LinearAlgebra]]
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+[[Markdown]]
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+[[Mmap]]
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+uuid = "77ba4419-2d1f-58cd-9bb1-8ffee604a2e3"
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+[[PDMats]]
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+[[Pkg]]
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+uuid = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
+
+[[PlotThemes]]
+deps = ["PlotUtils", "Requires", "Test"]
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+[[PlotUtils]]
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+
+[[Plots]]
+deps = ["Base64", "Contour", "Dates", "FixedPointNumbers", "GR", "JSON", "LinearAlgebra", "Measures", "NaNMath", "Pkg", "PlotThemes", "PlotUtils", "Printf", "REPL", "RecipesBase", "Reexport", "Requires", "Showoff", "SparseArrays", "StaticArrays", "Statistics", "StatsBase", "Test", "UUIDs"]
+git-tree-sha1 = "935241178e80158451cc33f4af7c57f671b881b8"
+uuid = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
+version = "0.19.3"
+
+[[Printf]]
+deps = ["Unicode"]
+uuid = "de0858da-6303-5e67-8744-51eddeeeb8d7"
+
+[[QuadGK]]
+deps = ["DataStructures", "LinearAlgebra", "Test"]
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+version = "2.0.2"
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+[[REPL]]
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+
+[[Random]]
+deps = ["Serialization"]
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+
+[[RecipesBase]]
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+[[Reexport]]
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+[[SparseArrays]]
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+[[SpecialFunctions]]
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+
+[[StatsModels]]
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+
+[[SuiteSparse]]
+deps = ["Libdl", "LinearAlgebra", "SparseArrays"]
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+
+[[Test]]
+deps = ["Distributed", "InteractiveUtils", "Logging", "Random"]
+uuid = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+
+[[TranscodingStreams]]
+deps = ["DelimitedFiles", "Pkg", "Random", "Test"]
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+
+[[URIParser]]
+deps = ["Test", "Unicode"]
+git-tree-sha1 = "6ddf8244220dfda2f17539fa8c9de20d6c575b69"
+uuid = "30578b45-9adc-5946-b283-645ec420af67"
+version = "0.4.0"
+
+[[UUIDs]]
+deps = ["Random"]
+uuid = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"
+
+[[Unicode]]
+uuid = "4ec0a83e-493e-50e2-b9ac-8f72acf5a8f5"
+
+[[WeakRefStrings]]
+deps = ["Missings", "Random", "Test"]
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diff --git a/Project.toml b/Project.toml
new file mode 100644
index 0000000..0b1f34d
--- /dev/null
+++ b/Project.toml
@@ -0,0 +1,19 @@
+name = "MomentOpt"
+uuid = "bc769cb7-f249-5bba-802a-79f18cb247ec"
+authors = ["Florian Oswald <florian.oswald@gmail.com>"]
+version = "0.1.0"
+
+[deps]
+DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
+DataFramesMeta = "1313f7d8-7da2-5740-9ea0-a2ca25f37964"
+DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
+Distributed = "8ba89e20-285c-5b6f-9357-94700520ee1b"
+Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
+Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
+FileIO = "5789e2e9-d7fb-5bc7-8068-2c6fae9b9549"
+GLM = "38e38edf-8417-5370-95a0-9cbb8c7f171a"
+JLD2 = "033835bb-8acc-5ee8-8aae-3f567f8a3819"
+Logging = "56ddb016-857b-54e1-b83d-db4d58db5568"
+PDMats = "90014a1f-27ba-587c-ab20-58faa44d9150"
+Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
+Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
diff --git a/src/MomentOpt.jl b/src/MomentOpt.jl
index 985f80c..85df003 100644
--- a/src/MomentOpt.jl
+++ b/src/MomentOpt.jl
@@ -1,31 +1,33 @@
 
 module MomentOpt
 
+__precompile__(false)
+
 # Dependencies
 # ############
 
+using Logging
 using Distributions 
-using MiniLogging
 using DataFrames, DataFramesMeta
-import Base.show, Base.std
+import Base.show 
+using Statistics
 using DataStructures
 using PDMats
 using Documenter
 using Plots
 using FileIO
 using JLD2
+using GLM
+using Distributed
 
 gr()
 
-# setup MiniLogging
-logger = get_logger()
-# if isinteractive()
-#     basic_config(MiniLogging.DEBUG; date_format="%H:%M:%S")
-# else
-    basic_config(MiniLogging.INFO; date_format="%H:%M:%S")
-# end
 
-import Base.get, Base.mean, Base.write, Base.start, Base.==
+# set log level
+LogLevel(Logging.Debug)
+
+import Base.get,Base.write, Base.start, Base.==
+import Statistics: mean
 
 # exports: Types
 export MProb, Eval,MAlgo, MAlgoBGP 
@@ -50,7 +52,8 @@ export addParam!,
        save,
        readMalgo,
        restartMOpt!,
-       extendBGPChain!
+       extendBGPChain!,
+       fitMirror
 
 
 
@@ -68,7 +71,7 @@ include("mopt/Examples.jl")
 include("mopt/plotting.jl")
 
 
-end 	# module
+end    # module
 
 
 
diff --git a/src/mopt/AlgoAbstract.jl b/src/mopt/AlgoAbstract.jl
index 80f2cc6..58dca20 100644
--- a/src/mopt/AlgoAbstract.jl
+++ b/src/mopt/AlgoAbstract.jl
@@ -24,7 +24,7 @@ function runMOpt!( algo::MAlgo )
 	# load data from file if set in algo.opts
 	# setup cluster if required
 
-	@info(logger,"Starting estimation loop.")
+	@info "Starting estimation loop."
 	t0 = time()
 
 	# do iteration
@@ -42,7 +42,7 @@ function runMOpt!( algo::MAlgo )
 				if haskey(algo.opts,"filename") == true
   				if mod(i,algo.opts["save_frequency"]) == 0
   					save(algo,algo.opts["filename"])
-  					@info(logger,"saved data at iteration $i")
+  					@info "saved data at iteration $i"
   				end
         end
 			end
@@ -58,13 +58,13 @@ function runMOpt!( algo::MAlgo )
 		save(algo,algo.opts["filename"])
 	else
     # if no filename is provided, generated a random number
-    filename = string(rand(1:Int(1e8)))
-		@warn(logger,"could not find 'filename' in algo.opts")
-    @warn(logger,"generated a random name instead: $(filename)")
-    save(algo,filename)
+    	filename,err = mktemp()
+		@warn "could not find 'filename' in algo.opts"
+    	save(algo,filename)
 	end
 
-	@info(logger,"Done with estimation after $t1 minutes")
+
+	@info "Done with estimation after $t1 minutes"
 
 	if get(algo.opts,"animate",false)
 		gif(algo.anim,joinpath(dirname(@__FILE__),"../../proposals.gif"),fps=2)
diff --git a/src/mopt/AlgoBGP.jl b/src/mopt/AlgoBGP.jl
index 253f85a..cb8350d 100644
--- a/src/mopt/AlgoBGP.jl
+++ b/src/mopt/AlgoBGP.jl
@@ -46,7 +46,7 @@ MCMC Chain storage for BGP algorithm.
 * `maxdist`: what's the maximal function value you will accept when proposed a swap. i.e. if ev.value > maxdist, you don't want to swap with ev.
 
 """
-type BGPChain <: AbstractChain
+mutable struct BGPChain <: AbstractChain
     evals     :: Array{Eval}
     best_id   :: Vector{Int}   # index of best eval.value so far
     best_val  :: Vector{Float64}   # best eval.value so far
@@ -68,7 +68,7 @@ type BGPChain <: AbstractChain
     function BGPChain(id::Int=1,n::Int=10,m::MProb=MProb(),sig::Vector{Float64}=Float64[],upd::Int64=10,upd_by::Float64=0.01,smpl_iters::Int=1000,maxdist::Float64=10.0,acc_tuner::Float64=2.0)
         @assert length(sig) == length(m.params_to_sample)
         this           = new()
-        this.evals     = Array{Eval}(n)
+        this.evals     = Array{Eval}(undef, n)
         this.best_val  = ones(n) * Inf
         this.best_id   = -ones(Int,n)
         this.curr_val  = ones(n) * Inf
@@ -166,7 +166,7 @@ function lastAccepted(c::BGPChain)
     if c.iter==1
         return 1
     else
-        return find(c.accepted[1:(c.iter)])[end]
+        return findall(c.accepted[1:(c.iter)])[end]
     end
 end
 getIterEval(c::BGPChain,i::Int) = c.evals[i]
@@ -216,7 +216,7 @@ function next_eval(c::BGPChain)
 
     # increment interation
     c.iter += 1
-    @debug(logger,"iteration = $(c.iter)")
+    @debug "iteration = $(c.iter)"
 
     # returns an OrderedDict
     pp = proposal(c)
@@ -237,8 +237,8 @@ end
 
 
 function doAcceptReject!(c::BGPChain,eval_new::Eval)
-            @debug(logger,"")
-            @debug(logger,"doAcceptReject!")
+            @debug ""
+            @debug "doAcceptReject!"
     if c.iter == 1
         # accept everything.
         eval_new.prob =1.0
@@ -257,10 +257,10 @@ function doAcceptReject!(c::BGPChain,eval_new::Eval)
             # this forumulation: old - new
             # because we are MINIMIZING the value of the objective function
             eval_new.prob = minimum([1.0,exp( c.acc_tuner * ( eval_old.value - eval_new.value) )]) #* (eval_new.value < )
-            @debug(logger,"eval_new.value = $(eval_new.value)")
-            @debug(logger,"eval_old.value = $(eval_old.value)")
-            @debug(logger,"eval_new.prob = $(round(eval_new.prob,2))")
-            @debug(logger,"c.probs_acc[c.iter] = $(round(c.probs_acc[c.iter],2))")
+            @debug "eval_new.value = $(eval_new.value)"
+            @debug "eval_old.value = $(eval_old.value)"
+            @debug "eval_new.prob = $(round(eval_new.prob,2))"
+            @debug "c.probs_acc[c.iter] = $(round(c.probs_acc[c.iter],2))"
 
             if !isfinite(eval_new.prob)
                 eval_new.prob = 0.0
@@ -269,7 +269,7 @@ function doAcceptReject!(c::BGPChain,eval_new::Eval)
 
             elseif !isfinite(eval_old.value)
                 # should never have gotten accepted
-                @debug(logger,"eval_old is not finite")
+                @debug "eval_old is not finite"
                 eval_new.prob = 1.0
                 eval_new.accepted = true
             else
@@ -281,9 +281,9 @@ function doAcceptReject!(c::BGPChain,eval_new::Eval)
                     eval_new.accepted = false
                 end
             end
-            @debug(logger,"eval_new.accepted = $(eval_new.accepted)")
-            @debug(logger,"")
-            @debug(logger,"")
+            @debug "eval_new.accepted = $(eval_new.accepted)"
+            @debug ""
+            @debug ""
 
         end
 
@@ -301,10 +301,10 @@ function doAcceptReject!(c::BGPChain,eval_new::Eval)
         # if mod(c.iter,c.sigma_update_steps) == 0
         #     too_high = c.accept_rate > 0.234
         #     if too_high
-        #         @debug(logger,"acceptance rate on BGPChain $(c.id) is too high at $(c.accept_rate). increasing variance of each param by $(100* c.sigma_adjust_by)%.")
+        #         @debug "acceptance rate on BGPChain $(c.id) is too high at $(c.accept_rate). increasing variance of each param by $(100* c.sigma_adjust_by)%.")
         #         set_sigma!(c,diag(c.sigma) .* (1.0+c.sigma_adjust_by) )
         #     else
-        #         @debug(logger,"acceptance rate on BGPChain $(c.id) is too low at $(c.accept_rate). decreasing variance of each param by $(100* c.sigma_adjust_by)%.")
+        #         @debug "acceptance rate on BGPChain $(c.id) is too low at $(c.accept_rate). decreasing variance of each param by $(100* c.sigma_adjust_by)%.")
         #         set_sigma!(c,diag(c.sigma) .* (1.0-c.sigma_adjust_by) )
         #     end
         # end
@@ -341,9 +341,9 @@ function proposal(c::BGPChain)
 
         # Transition Kernel is q(.|theta(t-1)) ~ TruncatedN(theta(t-1), Sigma,lb,ub)
         newp = OrderedDict(zip(collect(keys(mu)),mysample(MvNormal(collect(values(mu)),c.sigma),lb,ub,c.smpl_iters)))
-        # @debug(logger,"iteration $(c.iter)")
-        # @debug(logger,"old param: $(ev_old.params)")
-        # @debug(logger,"new param: $newp")
+        # @debug "iteration $(c.iter)")
+        # @debug "old param: $(ev_old.params)")
+        # @debug "new param: $newp")
 
         # flat kernel: random choice in each dimension.
         # newp = Dict(zip(collect(keys(mu)),rand(length(lb)) .* (ub .- lb)))
@@ -372,7 +372,7 @@ mutable struct MAlgoBGP <: MAlgo
 
         init_sd = OrderedDict{Symbol,Float64}()
         if opts["N"] > 1
-    		temps     = linspace(1.0,opts["maxtemp"],opts["N"])
+    		temps     = range(1.0,opts["maxtemp"],opts["N"])
             # initial std dev for each parameter to achieve at least bound_prob on the bounds
             # println("opts=$opts")
             # println("pars = $( m.params_to_sample)")
@@ -469,9 +469,9 @@ function computeNextIteration!( algo::MAlgoBGP )
         cs = pmap( x->next_eval(x), algo.chains ) # this does proposal, evaluateObjective, doAcceptRecject
     else
         # for i in algo.chains
-        #     @debug(logger," ")
-        #     @debug(logger," ")
-        #     @debug(logger,"debugging chain id $(i.id)")
+        #     @debug " ")
+        #     @debug " ")
+        #     @debug "debugging chain id $(i.id)")
         #     next_eval!(i)
         # end
         cs = map( x->next_eval(x), algo.chains ) # this does proposal, evaluateObjective, doAcceptRecject
@@ -511,9 +511,9 @@ function exchangeMoves!(algo::MAlgoBGP)
     samples = algo["N"] < 3 ? algo["N"]-1 : algo["N"]
     pairs = sample(props,samples,replace=false)
 
-    @debug(logger,"")
-    @debug(logger,"exchangeMoves: proposing pairs")
-    @debug(logger,"$pairs")
+    @debug ""
+    @debug "exchangeMoves: proposing pairs"
+    @debug "$pairs"
 
     for p in pairs
         i,j = p
@@ -522,20 +522,20 @@ function exchangeMoves!(algo::MAlgoBGP)
         # my version
         # if rand() < algo["mixprob"]
             # if (evj.value < evi.value)  # if j's value is better than i's
-            #     @debug(logger,"$j better than $i")
-            #     # @debug(logger,"$(abs(j.value)) < $(algo.chains[p[1]].maxdist)")
+            #     @debug "$j better than $i")
+            #     # @debug "$(abs(j.value)) < $(algo.chains[p[1]].maxdist)")
             #     # swap_ev!(algo,p)
             #     set_ev_i2j!(algo,i,j)
             # else
-            #     @debug(logger,"$i better than $j")
+            #     @debug "$i better than $j")
             #     set_ev_i2j!(algo,j,i)
             # end
         # end
 
         # BGP version
         # exchange i with j if rho(S(z_j),S(data)) < epsilon_i
-        @debug(logger,"Exchanging $i with $j? Distance is $(algo.dist_fun(evj.value - evi.value))")
-        @debug(logger,"Exchange: $(algo.dist_fun(evj.value - evi.value)  < algo["maxdists"][i])")
+        @debug "Exchanging $i with $j? Distance is $(algo.dist_fun(evj.value - evi.value))"
+        @debug "Exchange: $(algo.dist_fun(evj.value - evi.value)  < algo["maxdists"][i])"
         if algo.dist_fun(evj.value - evi.value)  < algo["maxdists"][i]
             swap_ev_ij!(algo,i,j)
         end
@@ -551,7 +551,7 @@ function exchangeMoves!(algo::MAlgoBGP)
 	# 			tmp = abs(e2.value - e1.value) / abs(e1.value)
 	# 			# tmp = abs(evals(algo.chains[ch2],algo.chains[ch2].i)[1] - oldval) / abs(oldval)	# percent deviation
 	# 			if tmp < dtol
- #                    @debug(logger,"perc dist $ch and $ch2 is $tmp. will label that `close`.")
+ #                    @debug "perc dist $ch and $ch2 is $tmp. will label that `close`.")
 	# 				push!(close,ch2)
 	# 			end
 	# 		end
@@ -559,7 +559,7 @@ function exchangeMoves!(algo::MAlgoBGP)
 	# 	# 2) with y% probability exchange with a randomly chosen BGPChain from close
 	# 	if length(close) > 0
 	# 		ex_with = rand(close)
-	# 		@debug(logger,"making an exchange move for BGPChain $ch with BGPChain $ex_with set: $close")
+	# 		@debug "making an exchange move for BGPChain $ch with BGPChain $ex_with set: $close")
 	# 		swap_ev!(algo,Pair(ch,ex_with))
 	# 	end
 	# end
@@ -567,7 +567,7 @@ function exchangeMoves!(algo::MAlgoBGP)
 end
 
 function set_ev_i2j!(algo::MAlgoBGP,i::Int,j::Int)
-    @debug(logger,"setting ev of $i to ev of $j")
+    @debug "setting ev of $i to ev of $j"
     ci = algo.chains[i]
     cj = algo.chains[j]
 
@@ -581,7 +581,7 @@ function set_ev_i2j!(algo::MAlgoBGP,i::Int,j::Int)
     set_exchanged!(ci,j)
 end
 function swap_ev_ij!(algo::MAlgoBGP,i::Int,j::Int)
-    @debug(logger,"swapping ev of $i with ev of $j")
+    @debug "swapping ev of $i with ev of $j"
     ci = algo.chains[i]
     cj = algo.chains[j]
 
@@ -619,7 +619,7 @@ function extendBGPChain!(chain::BGPChain, algo::MAlgoBGP, extraIter::Int64)
   #---------------------------------------
   # 1. Change the size:
   #--------------------
-  chain.evals    = Array{Eval}(finalIter)
+  chain.evals    = Array{Eval}(undef,finalIter)
   chain.best_val  = ones(finalIter) * Inf
   chain.best_id   = -ones(Int, finalIter)
   chain.curr_val  = ones(finalIter) * Inf
@@ -652,8 +652,8 @@ stopeed. Add extraIter additional steps to the optimization process.
 """
 function restartMOpt!(algo::MAlgoBGP, extraIter::Int64)
 
-  @info(logger,"Restarting estimation loop with $(extraIter) iterations.")
-  @info(logger,"Current best value on chain 1 before restarting $(MomentOpt.summary(algo)[:best_val][1])")
+  @info "Restarting estimation loop with $(extraIter) iterations."
+  @info "Current best value on chain 1 before restarting $(MomentOpt.summary(algo)[:best_val][1])"
   t0 = time()
 
   # Minus 1, to follow the MomentOpt convention
@@ -675,13 +675,13 @@ function restartMOpt!(algo::MAlgoBGP, extraIter::Int64)
 
   #change maxiter in the dictionary storing options
   #------------------------------------------------
-  @debug(logger, "Setting algo.opts[\"maxiter\"] = $(finalIter)")
+  @debug "Setting algo.opts[\"maxiter\"] = $(finalIter)"
   algo.opts["maxiter"] = finalIter
 
   # do iterations, starting at initialIter
   # and not at i=1, as in runMOpt!
   for i in initialIter:finalIter
-    @debug(logger,"iteration $(i)")
+    @debug "iteration $(i)"
 
     algo.i = i
 
@@ -711,7 +711,7 @@ function restartMOpt!(algo::MAlgoBGP, extraIter::Int64)
 				if haskey(algo.opts,"filename") == true
   				if mod(i,algo.opts["save_frequency"]) == 0
   					save(algo,algo.opts["filename"])
-  					@info(logger,"saved data at iteration $i")
+  					@info "saved data at iteration $i"
   				end
         end
 			end
@@ -725,14 +725,14 @@ function restartMOpt!(algo::MAlgoBGP, extraIter::Int64)
 		save(algo,algo.opts["filename"])
 	else
     # if no filename is provided, generated a random number
-    filename = string(rand(1:Int(1e8)))
-		@warn(logger,"could not find 'filename' in algo.opts")
-    @warn(logger,"generated a random name instead: $(filename)")
-    save(algo,filename)
+        filename = string(rand(1:Int(1e8)))
+		@warn "could not find 'filename' in algo.opts"
+        @warn "generated a random name instead: $(filename)"
+        save(algo,filename)
 	end
 
-	@info(logger,"Done with estimation after $t1 minutes")
-  @info(logger,"New best value on chain 1 = $(MomentOpt.summary(algo)[:best_val][1])")
+	@info "Done with estimation after $t1 minutes"
+    @info "New best value on chain 1 = $(MomentOpt.summary(algo)[:best_val][1])"
 
 	if get(algo.opts,"animate",false)
 		gif(algo.anim,joinpath(dirname(@__FILE__),"../../proposals.gif"),fps=2)
diff --git a/src/mopt/Eval.jl b/src/mopt/Eval.jl
index b8ddd85..63131c5 100644
--- a/src/mopt/Eval.jl
+++ b/src/mopt/Eval.jl
@@ -17,7 +17,7 @@
 * `options`: Dict of options and other info
 
 """ 
-type Eval
+mutable struct Eval
 
 	value        :: Float64
 	time         :: Float64
@@ -70,7 +70,7 @@ type Eval
 		for k in keys(p)
 			kk = Symbol(k)
             if length(p[k]) > 3
-                warn("you have a parameter with more tham 3 entries. we assume p = [val,lb,ub]")
+                @warn "you have a parameter with more tham 3 entries. we assume p = [val,lb,ub]"
             end
 			this.params[kk] = p[k][1] # we take the first one, in case there are several values per param
 			# not sure about that.
diff --git a/src/mopt/ObjExamples.jl b/src/mopt/ObjExamples.jl
index c68607e..3fdeb7d 100644
--- a/src/mopt/ObjExamples.jl
+++ b/src/mopt/ObjExamples.jl
@@ -67,7 +67,7 @@ function objfunc_norm(ev::Eval)
 	ns = 10000
 	sigma           = [1.0;1.0]
 	randMultiNormal = MomentOpt.MvNormal(mu,MomentOpt.PDiagMat(sigma)) 
-	simM            = mean(rand(randMultiNormal,ns),2)
+	simM            = mean(rand(randMultiNormal,ns),dims = 2)
 	simMoments = Dict(:mu1 => simM[1], :mu2 => simM[2])
 
 
@@ -106,7 +106,7 @@ function banana(ev::Eval)
 
     start(ev)
 	p = paramd(ev)
-    model = 100 .* (p["b"] - p["a"].^2 ).^2 .+ (1.-p["a"])^2
+    model = 100 .* (p["b"] - p["a"].^2 ).^2 .+ (1 .- p["a"])^2
     data  = 0.0
 
     setValue(ev,model)
diff --git a/src/mopt/econometrics.jl b/src/mopt/econometrics.jl
index 7050c15..f196b1d 100644
--- a/src/mopt/econometrics.jl
+++ b/src/mopt/econometrics.jl
@@ -27,7 +27,6 @@ Computes an approximation to the simulated score of moments at the optimal param
 
 """
 function score(MA::MAlgo)
-	using GLM
 
 	p = parameters_ID(MA.MChains)
 	inf = infos(MA.MChains)
diff --git a/src/mopt/incmopt.jl b/src/mopt/incmopt.jl
index f8efc16..fe3a7dd 100644
--- a/src/mopt/incmopt.jl
+++ b/src/mopt/incmopt.jl
@@ -1,4 +1,3 @@
-export fitMirror
 
 
 # transpose a 2-column dataframe to a one-row dataframe, so that 
@@ -159,7 +158,7 @@ function fitMirror!(x::DataFrame,b::Dict)
 end
 
 
-function findInterval{T<:Number}(x::T,vec::Array{T})
+function findInterval(x::T, vec::Array{T}) where T <: Number
 
     out = zeros(Int,length(x))
     sort!(vec)
diff --git a/src/mopt/mprob.jl b/src/mopt/mprob.jl
index 48f546a..f50ac45 100644
--- a/src/mopt/mprob.jl
+++ b/src/mopt/mprob.jl
@@ -26,7 +26,7 @@ of datamoments `moments`.
     ```
     
 """
-type MProb
+mutable struct MProb
 
   # setup
   initial_value       :: OrderedDict           # initial parameter value as a dict
@@ -41,7 +41,7 @@ type MProb
     this.initial_value       = OrderedDict()
     this.params_to_sample    = OrderedDict()
     function def(x)
-      info("default objfunc, returns input")
+      @info "default objfunc, returns input"
       x
     end
     this.objfunc             = def
@@ -145,7 +145,7 @@ function evaluateObjective(m::MProb,p::Union{Dict,OrderedDict})
        # ev = eval(Expr(:call,m.objfunc,ev))
       ev = m.objfunc(ev)
     catch ex
-      warn("caught exception $ex")
+      @warn "caught exception $ex"
       ev.status = -2
     end
     gc()
@@ -158,7 +158,7 @@ function evaluateObjective(m::MProb,ev)
        # ev = eval(Expr(:call,m.objfunc,ev))
        ev = m.objfunc(ev)
     catch ex
-      warn("caught exception $ex")
+      @warn "caught exception $ex"
       ev.status = -2
     end
     gc()
diff --git a/src/mopt/slices.jl b/src/mopt/slices.jl
index dd3b0f2..57e8d37 100644
--- a/src/mopt/slices.jl
+++ b/src/mopt/slices.jl
@@ -1,7 +1,6 @@
 
-# TODO
-# add plot slices
-type MyT
+
+mutable struct MyT
     data :: Dict
 end
 
@@ -20,7 +19,7 @@ export Slice,slices,add!,get
 """
     Slice 
 
-A *slice* in dimension ``j`` of a function ``f \in \mathbb{R}^N`` is defined as ``f(p[1],...,p[j],...,p[N])``, where `p` is the initial parameter vector and `p[j] = linspace(lower[j],upper[j],npoints)`, where `lower[j],upper[j]` are the bounds of the parameter space in dimension ``j``.
+A *slice* in dimension ``j`` of a function ``f ∈ \\mathbb{R}^N`` is defined as ``f(p[1],...,p[j],...,p[N])``, where `p` is the initial parameter vector and `p[j] = linspace(lower[j],upper[j],npoints)`, where `lower[j],upper[j]` are the bounds of the parameter space in dimension ``j``.
 
 ## Fields
 
@@ -36,11 +35,9 @@ julia> m = MProb()
 julia> p = OrderedDict(:p1=>1.1,:p2=>pi)
 julia> m = OrderedDict(:m1=>rand(),:m2=>e)
 julia> Slice(p,m)
-
 ```
-
 """
-type Slice
+mutable struct Slice
     res  :: Union{Dict,OrderedDict}    # result
     p0   :: Union{Dict,OrderedDict}    # initial param
     m0   :: Union{Dict,OrderedDict}    # data moments
@@ -118,7 +115,7 @@ function doSlices(m::MProb,npoints::Int,parallel=false,pad=0.1)
     
         # initialize eval
         ev = Eval(m,m.initial_value)
-        @info(logger,"slicing along $pp")
+        @info "slicing along $pp"
 
         if parallel
             vv = pmap( linspace(bb[:lb], bb[:ub], npoints) ) do pval
@@ -138,14 +135,14 @@ function doSlices(m::MProb,npoints::Int,parallel=false,pad=0.1)
 
         for v in vv 
             if (typeof(v) <: Exception)
-                warn("exception received. value not stored.")
+                @warn "exception received. value not stored."
             else
                 add!( res, pp, v)
             end
         end
     end  
     t1 = round((time()-t0)/60)
-    @info(logger,"done after $t1 minutes")
+    @info "done after $t1 minutes"
 
     return res 
 end
diff --git a/test/REQUIRE b/test/REQUIRE
index 4e217d8..a46c011 100644
--- a/test/REQUIRE
+++ b/test/REQUIRE
@@ -1,2 +1,2 @@
-TestSetExtensions
-DataFrames
\ No newline at end of file
+DataFrames
+DataStructures
diff --git a/test/include/test-include.jl b/test/include/test-include.jl
index 53a14de..132cf0d 100644
--- a/test/include/test-include.jl
+++ b/test/include/test-include.jl
@@ -18,7 +18,7 @@ function test_chain()
 end
 
 
-type MyP
+mutable struct MyP
     a :: Float64 
     b :: Float64 
 
diff --git a/test/runtests.jl b/test/runtests.jl
index 656695f..0dcab1a 100644
--- a/test/runtests.jl
+++ b/test/runtests.jl
@@ -1,9 +1,13 @@
 
 
 using MomentOpt
-using Base.Test
-using TestSetExtensions
+using Test
 using DataFrames
+using Distributed
+using Random
+using GLM
+using DataStructures
+using Statistics
 
 # If we want the test to pass, we need this
 # see https://github.com/JuliaPlots/Plots.jl/issues/1076
@@ -16,10 +20,15 @@ using DataFrames
 # Did you start 'gksqt'?""
 ENV["GKSwstype"] = "100"
 
-include(joinpath(dirname(@__FILE__),"include","test-include.jl"))
+dir = dirname(@__FILE__)
+include(joinpath(dir,"include","test-include.jl"))
 
-@testset ExtendedTestSet "Running MomentOpt tests" begin
+@testset "Running MomentOpt tests" begin
 
-    @includetests ARGS
+    include(joinpath(dir,"test_MProb.jl"))
+    include(joinpath(dir,"test_Eval.jl"))
+    # include(joinpath(dir,"test_slices.jl"))
+    # include(joinpath(dir,"test_AlgoAbstract.jl"))
+    include(joinpath(dir,"test_AlgoBGP.jl"))
 
 end
diff --git a/test/test_Eval.jl b/test/test_Eval.jl
index 0be72a8..ca447e2 100644
--- a/test/test_Eval.jl
+++ b/test/test_Eval.jl
@@ -63,18 +63,18 @@
 		@test ev.value == 4.2
 	end
 
-	@testset "testing saving/loading" begin
-		MomentOpt.FileIO.save("test5.jld2",Dict("ev"=>ev,"evs"=>[ev,ev2]))
-		sleep(1)
-		ev2_ = MomentOpt.FileIO.load("test5.jld2", "ev")
-		@test ev2_ == ev
-
-		evs = MomentOpt.FileIO.load("test5.jld2","evs")
-		@test evs[1] == ev
-		@test evs[2] == ev2
-		rm("test5.jld2")
-
-	end
+	# @testset "testing saving/loading" begin
+	# 	MomentOpt.FileIO.save("test5.jld2",Dict("ev"=>ev,"evs"=>[ev,ev2]))
+	# 	sleep(1)
+	# 	ev2_ = MomentOpt.FileIO.load("test5.jld2", "ev")
+	# 	@test ev2_ == ev
+
+	# 	evs = MomentOpt.FileIO.load("test5.jld2","evs")
+	# 	@test evs[1] == ev
+	# 	@test evs[2] == ev2
+	# 	rm("test5.jld2")
+
+	# end
 end
 
 
diff --git a/test/test_algoBGP.jl b/test/test_algoBGP.jl
index a554280..a1a49ed 100644
--- a/test/test_algoBGP.jl
+++ b/test/test_algoBGP.jl
@@ -62,12 +62,11 @@
 		addprocs(2)
 
 		@everywhere using MomentOpt
-		using GLM
-		using DataStructures
-		using DataFrames
-		using Plots
+		@everywhere using Statistics
+		@everywhere using MomentOpt
+
 
-		srand(1234)
+		Random.seed!(1234)
 
 		#------------------------
 		# initialize the problem:
@@ -115,7 +114,7 @@
 		    # draw ns observations from N([mu], sigma):
 		    randMultiNormal = MomentOpt.MvNormal(mu,MomentOpt.PDiagMat(sigma))
 		    # calculate the mean of the simulated data
-		    simM            = mean(rand(randMultiNormal,ns),2)
+		    simM            = mean(rand(randMultiNormal,ns),dims = 2)
 		    # store simulated moments in a dictionary
 		    simMoments = Dict(:mu1 => simM[1], :mu2 => simM[2])
 
@@ -248,12 +247,6 @@
 	# in the first place (keeping random shocks constant)
 	@testset "Testing stopping and restarting" begin
 
-		using MomentOpt
-		using GLM
-		using DataStructures
-		using DataFrames
-		using Plots
-
 		#------------------------
 		# initialize the problem:
 		#------------------------
@@ -292,10 +285,10 @@
 		    #sigma is set to be the identity matrix
 		    sigma = [1.0 ;1.0]
 		    # draw ns observations from N([mu], sigma):
-				srand(1234)
+			Random.seed!(1234)
 		    randMultiNormal = MomentOpt.MvNormal(mu,MomentOpt.PDiagMat(sigma))
 		    # calculate the mean of the simulated data
-		    simM            = mean(rand(randMultiNormal,ns),2)
+		    simM            = mean(rand(randMultiNormal,ns),dims = 2)
 		    # store simulated moments in a dictionary
 		    simMoments = Dict(:mu1 => simM[1], :mu2 => simM[2])
 
@@ -378,7 +371,7 @@
 
 
 		# set-up BGP algorithm:
-		srand(1234)
+		Random.seed!(1234)
 		MA = MAlgoBGP(mprob,opts)
 
 		# run the estimation
@@ -430,7 +423,7 @@
 
 
 		# set-up BGP algorithm:
-		srand(1234)
+		Random.seed!(1234)
 		MA2 = MAlgoBGP(mprob2,opts2)
 
 		# run the estimation: