Essays about: "Approximate Bayesian computation"

Found 5 essays containing the words Approximate Bayesian computation.

  1. 1. Delayed-acceptance approximate Bayesian computation Markov chain Monte Carlo: faster simulation using a surrogate model

    University essay from Göteborgs universitet/Institutionen för matematiska vetenskaper

    Author : Andrea Krogdal; [2020-01-09]
    Keywords : ABC; MCMC; delayed acceptance; DA; surrogate model;

    Abstract : The thesis introduces an innovative way of decreasing the computational cost of approximateBayesian computation (ABC) simulations when implemented via Markovchain Monte Carlo (MCMC). Bayesian inference has enjoyed incredible success sincethe beginning of 1990’s thanks to the re-discovery of MCMC procedures, and theavailability of performing personal computers. READ MORE

  2. 2. Calibration of Breast Cancer Natural History Models Using Approximate Bayesian Computation

    University essay from KTH/Matematisk statistik

    Author : Oscar Bergqvist; [2020]
    Keywords : Approximate Bayesian Computation; ABC; breast cancer natural history models; random effects; Bayesian statistics; likelihood-free inference; Approximate Bayesian computation; ABC; natural history models för bröstcancer; random effects; bayesiansk statistik; likelihood-fri inferens;

    Abstract : Natural history models for breast cancer describe the unobservable disease progression. These models can either be fitted using likelihood-based estimation to data on individual tumour characteristics, or calibrated to fit statistics at a population level. READ MORE

  3. 3. Summary Statistic Selection with Reinforcement Learning

    University essay from Uppsala universitet/Avdelningen för beräkningsvetenskap

    Author : Iliam Barkino; [2019]
    Keywords : Summary Statistics; Approximate Bayesian Computation; Reinforcement Learning; Machine Learning; Multi-Armed Bandit; Subset Selection; Minimizing Entropy; Approximate Sufficiency; Direct; Halving; SAR; OCBA-m; Racing;

    Abstract : Multi-armed bandit (MAB) algorithms could be used to select a subset of the k most informative summary statistics, from a pool of m possible summary statistics, by reformulating the subset selection problem as a MAB problem. This is suggested by experiments that tested five MAB algorithms (Direct, Halving, SAR, OCBA-m, and Racing) on the reformulated problem and comparing the results to two established subset selection algorithms (Minimizing Entropy and Approximate Sufficiency). READ MORE

  4. 4. Bayesian Parametrisation ofIn Silico Tumour Models

    University essay from Uppsala universitet/Institutionen för informationsteknologi

    Author : Jonas Radvilas Umaras; [2018]
    Keywords : ;

    Abstract : Technological progress in recent decades has allowed researchers to utilise accurate but computationally demanding models. One example of this development is the adoption of the multi-scale modelling technique for simulating various tissues. These models can then be utilised to test the efficacy of new drugs, e.g. READ MORE

  5. 5. Likelihood-free inference and approximate Bayesian computation for stochastic modelling

    University essay from Lunds universitet/Matematisk statistik

    Author : Oskar Nilsson; [2013]
    Keywords : Mathematics and Statistics;

    Abstract : With increasing model complexity, sampling from the posterior distribution in a Bayesian context becomes challenging. The reason might be that the likelihood function is analytically unavailable or computationally costly to evaluate. READ MORE