Comments (1)
Good catch!
Many apologies both for the delay and for the error.
Please note that this is a simple bug in the implementation of fib. The
correct code can be found here
http://www.robots.ox.ac.uk/~fwood/anglican/examples/viewer/?worksheet=aistats/branching-aistats.
For ease of reference I include it here
(defn fib [n]
"returns the n-th number in the Fibonacci sequence"
(loop [a 1 b 1 m 0](if %28= m n%29
a
%28recur b %28+ a b%29 %28inc m%29%29)))
Dr. Frank Wood
Associate Professor - Information Engineering, Oxford
Fellow - Kellogg College, Oxford
Fellow - Alan Turing Institute
Telephone: +441865283060
Web: http://www.robots.ox.ac.uk/~fwood
Email: [email protected]
Office: IEB 20.03
University of Oxford
Department of Engineering Science
Parks Road
Oxford
OX1 3PJ
Assistant: Maddy Crudge
Email: [email protected]
+44 1865 283058
Where: http://www.eng.ox.ac.uk/contact/how-to-reach-the-department
On Tue, Nov 8, 2016 at 9:03 PM, Kai Xu [email protected] wrote:
The branching model in the branching_aistats.clj file has some
non-deterministic error.(defn fib [n]
"returns the n-th number in the Fibonacci sequence"
(loop [a 0 b 1 m 0](if %28= m n%29
a
%28recur b %28+ a b%29 %28inc m%29%29)))(with-primitive-procedures [fib](defquery branching
"A simple example illustrating flow control with
dependence on random choices"
[]
%28let [count-prior %28poisson 4)
r (sample count-prior)
l (if (< 4 r)
6
(+ (fib (* 3 r))
(sample count-prior)))]
(observe (poisson l) 6)
(predict :r r)
(predict :l l))))If I run it with a lot of particles with SMC sampler, it sometimes give Error
during inference: org.apache.commons.math3.exception.NotStrictlyPositiveException:
mean (0) (but sometimes not). If the # of particles is large (say
500,000), it will be broken nearly every time.—
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