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By: | Dec 21, 2018 | Report Comment

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By: | Aug 05, 2014 | Report Comment

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By: | Aug 04, 2014 | Report Comment

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By: | Oct 26, 2013 | Report Comment

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By: | Oct 16, 2013 | Report Comment

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By: | Sep 13, 2013 | Report Comment

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By: | Sep 12, 2013 | Report Comment

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By: | Sep 07, 2013 | Report Comment

大致看了看，�常好的一份�料，�仅研究了Monte Carlo,还研究了Bayesian，�常值得大家看哦，�过缺点就在于这份PDF没有目录，所以我为这个�料�了一份目录，希望�以帮助大家学习：Monte Carlo Statistical Methods by Christian P.Robertcontext1 introduction 1.1 Statistical Models 5 1.2 Likelihood Methods 10 1.3 Bayesian Methods 21 1.4 Deterministic Numerical Methods 28 1.5 siomtaliun versus numerical analysis: when is it useful? 312 Random Variable Generation 35 2.1 Basic Methods 37 2.2 Beyond uniform distributions 513 Monte Carlo Intergration 76 3.1 introduction 77 3.2 Classical Monte Carlo Integration 80 3.3 importance sampling 87 3.4 Acceleration Methods 984 Markov Chains 108 4.1 Basic Notions 110 4.2 Irreducibility 115 4.3 Transience/Recurrence 123 4.4 Invariant Measures 126 4.5 Ergodicity and stationarity 130 4.6 Limit Theorems 1345 Monte Carlo Optimization 139 5.1 Introduction 140 5.2 Stochastic Exploration 142 5.3 Stochastic Approximation 173 5.3.3 MCEM 1956 The Metropolis-Hastings Algorithm 6.1 Markov Chain Monte Carlo 197 6.2 The Metropolis-Hastings Algorithm 199 6.3 A Collection of Metropolis-Hastings Algorithms 204 6.4 Extensions 2177 The Gibbs Sampler 231 7.1 General Principles 232 7.1.5 Hierarchical models 253 7.2 Data Augmentation 255 7.3 Improper Priors 2718 Diagnosing Convergence 278 8.1 Stopping the Chain 279 8.2 Monitoring Stationarity Convergence 282 8.3 Monitoring Average Convergence 2909 Implementation in Missing Data Models 317 9.1 First examples 319 9.2 Finite mixtures of distributions 340 9.3 Extensions 354

By: | Dec 05, 2012 | Report Comment

I've implemented your code in Erlang. Seems very slow since the recisruon means many of the nodes are calculated multiple times. This increases dramatically with an increase in N. Any ideas of how to make it more efficient? Does Haskell make it efficient automatically?-module(crr).-import(math, [sqrt/1, exp/1, pow/2]).-export([optionPrice/6]).max(X, Y) when X > Y -> X;max(_X, Y) -> Y.optionPrice(S, K, T, R, V, N) -> Dt = T / N, U = exp(V * sqrt(Dt)), D = 1 / U, P = (exp(R * Dt) D) / (U D), f(0, 0, S, K, R, Dt, U, P, N).s(J, S, U) -> S * pow(U, J).f(N, J, S, K, _R, _Dt, U, _P, N) -> Sij= s(J, S, U), max(Sij K, 0);f(I, J, S, K, R, Dt, U, P, N) -> Sij= s(J, S, U), Vij = exp(-R * Dt) * (P * f(I + 1, J + 1, S, K, R, Dt, U, P, N) + (1 P) * f(I + 1, J 1, S, K, R, Dt, U, P, N)), max(Sij K, Vij).calling the function:(emacs@localhost)13> crr:optionPrice(100,100,1,0.05,0.3,25).14.341546969779252riskyrisk

By: | Nov 18, 2012 | Report Comment

. I just saw enough crap to know Ryan was being dumb. Yeah there was some silly stuff where McI and Ryan were trniyg to blame issues on their paper with a direction they think ES steered it. I fastened on that quickly as did you and ES, and of course it is sill, those guys are responsible for their published work, not the reviewer. McI has a bad habit of that sillines with previous papers. I think a lot of the issue comes from them being so disorganized in blog writing and then sending in review drafts that are a mash of different variables in a non full factorial manner. They just don't think clearly in terms of disaggregation in their analyses. I saw it, but there's only so many hours in the day, did not bother nailing it.Other guy: It's been discussed a lot. Start with the 2005 Huybers comment on McI's 2005 paper. It's a very easy read and H even shows the formula so you can see how McI changed two paramaters at once (but did not report a full factorial). No OFAT. No full factorial. Just two equations with three unknowns (two independ variables, and one dependent).

By: | Sep 29, 2012 | Report Comment

I think youve produced some truly inisreettng points. Not also many people would truly think about this the way you just did. Im seriously impressed that theres so much about this subject thats been uncovered and you did it so well, with so very much class. Great 1 you, man! Genuinely fantastic stuff right here.

By: | Apr 29, 2012 | Report Comment

fifl 2010

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