by freefrancisco on 12/31/15, 6:44 AM with 94 comments
by ozgooen on 12/31/15, 8:00 AM
by aj7 on 1/1/16, 5:56 AM
Of special interest are non-continuous distributions. How often have normal distribution reasoning failed in finance? Put another way, a user should be able to model a distribution himself.
by hardmath123 on 1/1/16, 1:52 AM
http://research.microsoft.com/pubs/208236/asplos077-bornholt...
by imh on 12/31/15, 10:56 PM
by p4bl0 on 12/31/15, 9:35 PM
by krmmalik on 12/31/15, 10:01 PM
by kadder on 1/1/16, 12:54 PM
As per the paper , you can choose arbitrary distributions , construct a fluent graph , run Monte Carlo simulation and get the result - |via http://bit.ly/hnbuzz01 |
by sundarurfriend on 1/1/16, 5:54 PM
Perhaps that field can provide a potential source of new names, when you decide to market this as a company.
by jkaptur on 12/31/15, 10:37 PM
by brudgers on 12/31/15, 3:54 PM
by evanb on 12/31/15, 11:28 PM
How does one tell guesstimate that there's a hard lower bound on a quantity. ie. Video Length is at least 0, because negative watch times are unphysical? I know the specified distribution in this case is very narrow (the video lasting between -1 and 0 minutes has probability ~0.000032). But the answer does come out to be 26±32, which includes a substantial unphysical region.
And, if I give a hard lower bound on Video Length, can it propagate that knowledge into an asymmetric error on Total time?
by jakespencer on 12/31/15, 9:31 PM
by jasonshen on 12/31/15, 8:52 PM
by jeffehobbs on 12/31/15, 9:12 PM
by Mauricio_ on 1/1/16, 2:08 AM
by marcusgarvey on 12/31/15, 9:39 PM
http://www.theatlantic.com/politics/archive/2014/03/rumsfeld...
by tunesmith on 12/31/15, 8:38 PM
by miguelrochefort on 1/1/16, 9:41 AM
Surely, such a platform would make building an app 100 times easier. Not that building apps is a good use of our resources.
by conservajerk on 12/31/15, 9:06 PM
by netghost on 12/31/15, 10:21 PM
You might consider upping the run count, or maybe narrowing your bins for the visualization. Either way, it's great to see more tools embracing probability and uncertainty like this.
by ashish161 on 1/1/16, 11:00 AM
image link https://camo.githubusercontent.com/8fd97a97fa656a1eb92294f0f...
by evanb on 1/1/16, 12:46 AM
by desireco42 on 1/1/16, 7:00 PM
by Beltiras on 1/1/16, 1:00 AM
by retube on 1/1/16, 12:51 AM
by rbanffy on 12/31/15, 9:12 PM
by Chris2048 on 12/31/15, 11:19 AM
Also check out:
http://probcomp.csail.mit.edu/bayesdb/
https://github.com/taschini/pyinterval http://mavrinac.com/index.cgi?page=fuzzpy