diff --git a/Project.toml b/Project.toml
new file mode 100644
index 0000000..7362a9f
--- /dev/null
+++ b/Project.toml
@@ -0,0 +1,20 @@
+name = "BIGUQ"
+uuid = "7f9c7709-75fb-5397-acba-f980073965f6"
+version = "0.6.0"
+
+[deps]
+AffineInvariantMCMC = "a0f608ac-68d0-5108-ad9a-0cdca73324f3"
+BlackBoxOptim = "a134a8b2-14d6-55f6-9291-3336d3ab0209"
+DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
+Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
+ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
+RobustPmap = "27aeedcb-f738-516b-a0b8-3211cf1146e5"
+
+[compat]
+julia = "≥ 1.0.0"
+
+[extras]
+Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+
+[targets]
+test = ["Test"]
\ No newline at end of file
diff --git a/REQUIRE b/REQUIRE
index 49b2692..ba496a4 100644
--- a/REQUIRE
+++ b/REQUIRE
@@ -1,8 +1,7 @@
-julia 0.6 1.0
+julia 1.0
 RobustPmap
 AffineInvariantMCMC
 DataFrames
 ForwardDiff
 BlackBoxOptim
-Klara 0.8.6
 Distributions
diff --git a/src/BIGOED.jl b/src/BIGOED.jl
index fb4f02d..2be6e82 100644
--- a/src/BIGOED.jl
+++ b/src/BIGOED.jl
@@ -96,22 +96,22 @@ function generateproposedobs(bigoed::BigOED, proposedindex::Int, numobsrealizati
 		return retval
 	end
 	#mcmcmodel = Klara.model(loglikelihood, init=bigoed.nominalparams)
-	mcmcparams = Klara.BasicContMuvParameter(:p, logtarget=loglikelihood)
-	mcmcmodel = Klara.likelihood_model(mcmcparams, false)
+	# mcmcparams = Klara.BasicContMuvParameter(:p, logtarget=loglikelihood)
+	# mcmcmodel = Klara.likelihood_model(mcmcparams, false)
 	#=
 	if Base.isbindingresolved(Klara, :RAM)
 		mcmcsampler = Klara.RAM(fill(1e-1, length(bigoed.nominalparams)), 0.3)
 	else
 		warn("Robust Adaptive Metropolis (RAM) method is not available")
 		=#
-		mcmcsampler = Klara.MH(fill(1e-1, length(bigoed.nominalparams)))
+		# mcmcsampler = Klara.MH(fill(1e-1, length(bigoed.nominalparams)))
 	#end
-	mcmcrange = Klara.BasicMCRange(nsteps=thinning * numobsrealizations + burnin, burnin=burnin, thinning=thinning)
+	# mcmcrange = Klara.BasicMCRange(nsteps=thinning * numobsrealizations + burnin, burnin=burnin, thinning=thinning)
 	mcmcparams0 = Dict(:p=>bigoed.nominalparams)
 	outopts = Dict{Symbol, Any}(:monitor=>[:value, :logtarget, :loglikelihood], :diagnostics=>[:accept])
-	job = Klara.BasicMCJob(mcmcmodel, mcmcsampler, mcmcrange, mcmcparams0, outopts=outopts, tuner=Klara.VanillaMCTuner())
-	Klara.run(job)
-	mcmcchain = Klara.output(job)
+	# job = Klara.BasicMCJob(mcmcmodel, mcmcsampler, mcmcrange, mcmcparams0, outopts=outopts, tuner=Klara.VanillaMCTuner())
+	# Klara.run(job)
+	# mcmcchain = Klara.output(job)
 	#use the mcmc samples to generate realizations of the proposed obs
 	proposedlocations = bigoed.proposedlocations[proposedindex]
 	proposedtimes = bigoed.proposedtimes[proposedindex]
diff --git a/src/BIGUQ.jl b/src/BIGUQ.jl
index a02cac4..e4d3c26 100644
--- a/src/BIGUQ.jl
+++ b/src/BIGUQ.jl
@@ -32,7 +32,6 @@ LA-CC-15-080; Copyright Number Assigned: C16008
 module BIGUQ
 
 import DataFrames
-import Klara
 import ForwardDiff
 import BlackBoxOptim
 import Distributions
diff --git a/test/runtests.jl b/test/runtests.jl
index 7659afd..d6b86d0 100644
--- a/test/runtests.jl
+++ b/test/runtests.jl
@@ -1,5 +1,5 @@
-using Base.Test
+import Test
 
-@assert(1 == 1)
+@Test.test 1 == 1
 
 :passed
\ No newline at end of file