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Approximate Bayesian computation (ABC): advances and questions
Published on Aug 22, 201212500 Views
The lack of closed formlikelihoods has been the bane of Bayesian computation for many years and, prior to the introduction of MCMC methods, a strong impediment to the propagation of the Bayesian para
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Approximate Bayesian Computation: how Bayesian can it be?00:00
This talk is dedicated to the memory of our dear friend and fellow Bayesian, George Casella, 1951{201202:17
Outline02:57
Approximate Bayesian computation03:47
General issue04:08
Monte Carlo basics (1)04:29
Monte Carlo basics (2)04:48
Importance Sampling (1)05:04
Importance Sampling (2)05:29
Importance Sampling (convergence) (1)05:44
Importance Sampling (convergence) (2)05:50
Self-normalised importance Sampling (1)06:05
Self-normalised importance Sampling (2)06:18
Self-normalised importance Sampling (3)06:25
Perspectives (1)06:58
Perspectives (2)07:38
Perspectives (3)07:42
Econom'ections09:03
Simulated method of moments (1)10:08
Simulated method of moments (2)10:57
Method of simulated moments11:13
Indirect inference12:10
Indirect inference (PML vs. PSE) (1)13:24
Indirect inference (PML vs. PSE) (2)13:56
Consistent indirect inference (1)14:05
Consistent indirect inference (2)14:09
Choice of pseudo-model15:21
Empirical likelihood (1)16:56
Empirical likelihood (2)18:56
ABCel19:47
A?B?C? (1)20:58
A?B?C? (2)21:08
A?B?C? (3)21:19
How much Bayesian?21:31
Approximate Bayesian computation23:02
Genetic background of ABC23:14
Demo-genetic inference (1)24:01
Demo-genetic inference (2)24:21
A genuine example of application24:37
Alternative scenarios25:10
Untractable likelihood (1)25:36
Untractable likelihood (2)25:56
Untractable likelihood (3)25:59
Untractable likelihood (4)26:49
ABC methodology (1)27:01
ABC methodology (2)27:04
ABC methodology (3)27:15
Why does it work?!29:01
A as A...pproximative (1)29:52
A as A...pproximative (2)30:15
ABC algorithm30:19
Output (1)31:31
Output (2)31:35
Output (3)31:59
Convergence of ABC ( first attempt) (1)32:01
Convergence of ABC ( first attempt) (2)32:04
Convergence of ABC ( first attempt) (3)32:19
Convergence of ABC ( first attempt) (4)32:20
Convergence of ABC (second attempt) (1)32:21
Convergence of ABC (second attempt) (2)32:22
Convergence (do not attempt!) (1)32:22
Convergence (do not attempt!) (2)32:32
Convergence (do not attempt!) (3)32:42
Convergence (do not attempt!) (4)33:01
Probit modelling on Pima Indian women (1)33:27
Probit modelling on Pima Indian women (2)33:30
Probit modelling on Pima Indian women (3)33:31
Probit modelling on Pima Indian women (4)33:32
Pima Indian benchmark33:33
MA example (1)33:34
MA example (2)34:10
MA example (3)34:23
MA example (4)34:52
Comparison of distance impact (1)36:14
Comparison of distance impact (2)37:41
Comparison of distance impact (3)38:29
Comments38:44
ABC (simul') advances (1)40:46
ABC (simul') advances (2)41:04
ABC (simul') advances (3)41:05
ABC (simul') advances (4)41:06
ABC-NP41:15
ABC-NP (regression) (1)42:07
ABC-NP (regression) (2)42:33
ABC-NP (density estimation) (1)43:06
ABC-NP (density estimation) (2)43:19
ABC-NP (density estimations) (1)43:20
ABC-NP (density estimations) (2)43:37
ABC inference machine44:17
How much Bayesian? (1)44:35
How much Bayesian? (2)46:02
ABCμ (1)46:14
ABCμ (2)46:14
ABCμ (3)46:15
ABCμ details (1)47:21
ABCμ details (2)47:24
ABCμ multiple errors48:19
ABCμ for model choice48:59
Questions about ABCμ [and model choice] (1)49:01
Questions about ABCμ [and model choice] (2)49:02
Wilkinson's exact BC (not exactly!) (1)49:03
Wilkinson's exact BC (not exactly!) (2)50:12
How exact a BC? (1)51:20
How exact a BC? (2)51:44
ABC for HMMs (1)52:10
ABC for HMMs (2)52:11
ABC-MLE for HMMs (1)53:22
ABC-MLE for HMMs (2)53:24
ABC-MLE is biased (1)54:28
ABC-MLE is biased (2)54:44
Noisy ABC-MLE55:16
Consistent noisy ABC-MLE56:16
Which summary? (1)56:49
Which summary? (2)56:59
Which summary? (3)57:06
Which summary for model choice? (1)58:06
Which summary for model choice? (2)58:15
Semi-automatic ABC58:44
Summary [of F&P/statistics) (1)59:15
Summary [of F&P/statistics) (2)01:00:23
Details on Fearnhead and Prangle (F&P) ABC01:00:24
Errors, errors, and errors01:00:27