Essays about: "Bayesian statistics"
Showing result 6 - 10 of 67 essays containing the words Bayesian statistics.
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6. Application of Bootstrap in Approximate Bayesian Computation (ABC)
University essay from Uppsala universitet/Statistik, AI och data scienceAbstract : 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
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7. Spatial modeling with INLA for analysis of unequal care in Skåne
University essay from Lunds universitet/Matematisk statistikAbstract : The objective of this thesis is to extend on a previous analysis of health care accessibility for patients diagnosed with a chronic disease in Region Skåne. The previous analysis resulted in a logistic mixed effects model having municipality as a random effect and age as a first-degree spline-function. READ MORE
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8. Dynamic Covariance Modelling Using Generalised Wishart Processes
University essay from Lunds universitet/Matematisk statistikAbstract : Modern portfolio theory was pioneered by Markowitz who formulated the mean-variance problem, without which any discussion on quantitative approaches to portfolio selection would be incomplete. The framework boils down to finding the expected return $\mu$ and covariance $\Sigma$, after which the solution is proportional to $\Sigma^{-1}\mu$. READ MORE
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9. Probabilistic settlement analysis for embankments using preloading without surcharge
University essay from KTH/Jord- och bergmekanikAbstract : Preloading without a surcharge is a common method for ground improvement. Thereare however uncertainties related to the number of site investigations and the partialfactor method has been identified as a problem. READ MORE
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10. Towards Deep Learning Accelerated Sparse Bayesian Frequency Estimation
University essay from Lunds universitet/Matematisk statistikAbstract : The Discrete Fourier Transform is the simplest way to obtain the spectrum of a discrete complex signal. This thesis concerns the case when the signal is known to contain a small (unknown) number of frequencies, not limited to the discrete Fourier frequencies, embedded in complex Gaussian noise. READ MORE