Module Expr Str ImportFrom alias ImportFrom alias ImportFrom alias Assign NameStore Call NameLoad Num Num Num Assign NameStore Lambda arguments args NameParam defaults BinOpMult Call NameLoad NameLoad NameLoad Assign NameStore TupleLoad TupleLoad Num UnaryOpUSub NameLoad TupleLoad Num NameLoad Assign NameStore Num Assign NameStore BinOpAdd Call NameLoad TupleLoad Num Num BinOpMult Call NameLoad AttributeLoad NameLoad attr NameLoad Assign NameStore Num Assign NameStore Call NameLoad keyword NameLoad keyword NameLoad keyword NameLoad keyword NameLoad keyword ListLoad Str Str Assign NameStore Call NameLoad keyword NameLoad keyword Call NameLoad BinOpMult Num NameLoad Num NameLoad keyword Num keyword Num Assign NameStore Call AttributeLoad NameLoad attr Assign AttributeStore NameLoad attr Str Expr Call AttributeLoad NameLoad attr Lambda arguments args NameParam defaults BinOpAdd SubscriptLoad NameLoad Index Num SubscriptLoad NameLoad Index Num keyword ListLoad Str ImportFrom alias Assign NameStore Call NameLoad NameLoad NameLoad keyword Num keyword NameLoad Expr Call NameLoad Str SubscriptLoad AttributeLoad NameLoad attr Index Num SubscriptLoad AttributeLoad NameLoad attr Index Num Assign TupleStore NameStore NameStore Call AttributeLoad NameLoad attr keyword Num Expr Call NameLoad Str Call NameLoad SubscriptLoad NameLoad ExtSlice Slice Index Num Call NameLoad SubscriptLoad NameLoad ExtSlice Slice Index Num keyword Num Expr Call NameLoad NameLoad keyword Num Expr Call NameLoad
N/A N/A 
Example model with strong correlations between the fitted parameters.

We use a*x = y + N(0,1) made complicated by defining a=p1+p2.

The expected distribution for p1 and p2 will be uniform, with p2 = a-p1 in
each sample.  Because this distribution is inherently unbounded, artificial
bounds are required on a least one of the parameters for finite duration
simulations.

The expected distribution for p1+p2 can be determined from the linear model
y = a*x.  This is reported along with the values estimated from MCMC.
 __future__ print_function pylab * dream * N/A x N/A linspace -1.0 1 40 N/A fn N/A N/A N/A p N/A N/A N/A sum p x N/A bounds N/A N/A -20 N/A inf N/A 40 inf N/A sigma 1 N/A data N/A N/A fn N/A 1 1 N/A N/A randn N/A x shape sigma N/A n 2 N/A model N/A Simulation f fn data data sigma sigma bounds bounds labels N/A x y N/A sampler N/A Dream model model population N/A randn N/A 5 n 4 n thinning 1 draws 20000 N/A mc N/A N/A sampler sample N/A N/A mc title Strong anti-correlation N/A N/A N/A mc derive_vars N/A N/A N/A p N/A N/A N/A p N/A 0 N/A p N/A 1 labels N/A x+y bumps.wsolve wpolyfit N/A poly N/A wpolyfit x data degree 1 origin True N/A N/A print x+y from linear fit N/A N/A poly coeff N/A 0 N/A N/A poly std N/A 0 N/A N/A points logp N/A N/A mc sample portion 0.5 N/A N/A print x+y from MCMC N/A mean N/A points N/A N/A N/A 2 N/A std N/A points N/A N/A N/A 2 ddof 1 N/A N/A plot_all mc portion 0.5 N/A N/A show