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Showing result 1 - 5 of 9 essays matching the above criteria.

  1. 1. Parameter Inference for Stochastic Models of Gene Expression in Eukaryotic Cells

    University essay from Uppsala universitet/Institutionen för informationsteknologi

    Author : Ansar Siddiqui; [2023]
    Keywords : ;

    Abstract : Simulation models are often used to study a system or phenomenon. However, before a simulation model can be used, its parameter needs to be fit to mimic observed data. This is called the parameter inference problem. READ MORE

  3. 2. Approximate Bayesian Computation for Data-Driven Epidemiological Models

    University essay from Uppsala universitet/Institutionen för informationsteknologi

    Author : Christoph Nötzli; [2023]
    Keywords : ;

    Abstract : Epidemiological models can help us to understand the spread of pathogens in a population. Fitting these mathematical models to epidemiological data can be a difficult task due to uncertain or missing data. READ MORE

  4. 3. Application of Bootstrap in Approximate Bayesian Computation (ABC)

    University essay from Uppsala universitet/Statistik, AI och data science

    Author : Ellinor Nyman; [2023]
    Keywords : ABC; Bootstrap; Computer intensive methods; Bayesian statistics; Linear regression;

    Abstract : The ABC algorithm is a Bayesian method which simulates samples from the posterior distribution. In this thesis, the method is applied on both synthetic and observed data of a regression model. Under normal error distribution a conjugate prior and the likelihood function are used in the algorithm. READ MORE

  5. 4. Data-driven Discovery of Real-time Road Compaction Parameters

    University essay from KTH/Matematisk statistik

    Author : Yuqi Shao; [2022]
    Keywords : statistics; machine learning; road compaction; statistik; maskininlärning; vägpackning;

    Abstract : Road compaction is the last and important stage in road construction. Both under-compaction and over-compaction are inappropriate and may lead to road failures. Intelligent compactors has enabled data gathering and edge computing functionalities, which introduces possibilities in data-driven compaction control. READ MORE

  6. 5. 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 approximate Bayesian computation (ABC) simulations when implemented via Markov chain Monte Carlo (MCMC). Bayesian inference has enjoyed incredible success since the beginning of 1990’s thanks to the re-discovery of MCMC procedures, and the availability of performing personal computers. READ MORE