Timeline for Var self-normalised sampling estimator

13 events

when toggle format	what		by	license	comment
Dec 13, 2016 at 9:52	history	edited	Motmot	CC BY-SA 3.0	deleted 3 characters in body
Dec 12, 2016 at 22:49	history	edited	Motmot	CC BY-SA 3.0	edited title
Dec 12, 2016 at 22:47	history	rollback	Motmot		Rollback to Revision 2
Dec 12, 2016 at 22:45	history	edited	Motmot	CC BY-SA 3.0	edited title
Dec 12, 2016 at 22:42	vote	accept	Motmot
Dec 12, 2016 at 18:26	answer	added	Mark L. Stone		timeline score: 2
Dec 12, 2016 at 0:30	comment	added	Mark L. Stone		To get a more accurate estimate than the Delta Method, use bootstrapping. As a bonus, that will give you an estimate of the entire distribution. However if you want to get an estimate of variance without (prior to) having data, then use the Delta Method.
Dec 11, 2016 at 21:05	answer	added	Xi'an		timeline score: 2
Dec 11, 2016 at 20:55	answer	added	Taylor		timeline score: 8
Dec 11, 2016 at 19:42	history	edited	kjetil b halvorsen♦	CC BY-SA 3.0	added 3 characters in body
Dec 11, 2016 at 17:55	comment	added	Motmot		I don't know the Delta method. I have the vector x of n realization of the instrumental r.v., i have computed the vector wi (of dimension n) with the importance weights, I have estimated the parameter with that summation but I need an estimate of the variance/error of this estimate.
Dec 11, 2016 at 17:36	comment	added	Xi'an		There is no closed-form solution for the variance, due to the self-normalising term, but only (asymptotic) approximations by the Delta method.
Dec 11, 2016 at 16:26	history	asked	Motmot	CC BY-SA 3.0