- Видео 8
- Просмотров 1 344
Richard Everitt
Добавлен 22 дек 2010
Reader in the Statistics Department at the University of Warwick. richardgeveritt.github.io/
IEnKI-ABC, likelihood estimation on a "bad" point
This video illustrates the algorithm that estimates the likelihood, on data from the stochastic Lotka-Volterra model in a new ABC method (IEnKI-ABC). Here we examine the refinement of simulations from the model for parameters *not* in the typical set of the posterior.
Просмотров: 36
Видео
IEnKI-ABC, likelihood estimation on a "good" point
Просмотров 48Год назад
This video illustrates the algorithm that estimates the likelihood, on data from the stochastic Lotka-Volterra model in a new ABC method (IEnKI-ABC). Here we examine the refinement of simulations from the model for parameters in the typical set of the posterior.
Rare event ABC-SMC^2
Просмотров 182 года назад
An illustration of the ABC-SMC^2 algorithm with two particles for three iterations, with one particle being updated using a rare event ABC-MCMC move, as described in Prangle et al. (2018) (link.springer.com/article/10.1007/s11222-017-9764-4). Each particle has its own draws from the model, which are represented by black dots. A uniform ABC kernel is used, with the region of non-zero density for...
An illustration of ABC-SMC
Просмотров 832 года назад
An illustration of an ABC-SMC algorithm with two particles for three iterations, with one particle being updated using an ABC-MCMC move. Each particle has its own draws from the model, which are represented by black dots. A uniform ABC kernel is used, with the region of non-zero density for this kernel being represented by the red circle. Note that once the draws from the model (the black dots)...
Statistical Learning and Big Data End Credits
Просмотров 1913 года назад
Statistical Learning and Big Data End Credits
Inferring a tree online using sequential Monte Carlo
Просмотров 1336 лет назад
This video shows the evolution, as sequences are added, of the majority rule consensus tree found by an SMC algorithm. The most recently added sequence is highlighted in each case. The position in which the new branch is added is determined by a proposal distribution based on SNP differences. The SMC then uses MCMC moves at a number of "intermediate distributions" to update the proposed branch,...
I watched the whole thing, this changed my life for the greater good
10/10
BEST CIDEO EVER