Essays about: "conditional models"
Showing result 1 - 5 of 191 essays containing the words conditional models.
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1. Predicting Counter-Strike Matches using Machine Learning Models
University essay from Lunds universitet/Statistiska institutionenAbstract : Sports betting is a widespread industry where predictive modeling play a big role. The goal of this thesis is to explore the possibilities of machine learning within the realm of e-sport prediction. The data used for this thesis is publicly available data was recorded over a three year period. READ MORE
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2. Spatio-temporal analysis of COVID-19 in Västra Götaland, Sweden
University essay from Göteborgs universitet/Institutionen för matematiska vetenskaperAbstract : Spatio-temporal analysis of COVID-19 data with the two different statistical approaches is the main objective of this thesis. The first classical approach, the Endemic-Epidemic framework (Held et al., 2005) is a class of multivariate time-series models for the incidence counts, obtained from the surveillance systems. READ MORE
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3. Volatility Forecasting - A comparative study of different forecasting models.
University essay fromAbstract : This study evaluates the out-of-sample forecasting performance of different volatility mod- els. When applied to XACT OMXS30, we use GARCH(1,1), EGARCH(1,1), and t- GAS(1,1) to forecast squared daily returns while Realized GARCH(1,1) and HAR-RV are used to forecast Realized Variance. READ MORE
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4. Value at Risk Estimation using GARCH Family Models: A Comparison of Different Specifications and Distributions.
University essay from Göteborgs universitet/Institutionen för nationalekonomi med statistikAbstract : The objective of this study is to compare the performance of different GARCH models, under various conditional distribution assumptions, to predict one-day-ahead Value-at-Risk (VaR) for three stocks: Swedbank, Handelsbanken, and SEB over the Covid-19 period. The performance is evaluated using Kupiec, Christoffersen tests and the Quadratic Loss. READ MORE
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5. Uncertainty Estimation in Radiation Dose Prediction U-Net
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : The ability to quantify uncertainties associated with neural network predictions is crucial when they are relied upon in decision-making processes, especially in safety-critical applications like radiation therapy. In this paper, a single-model estimator of both epistemic and aleatoric uncertainties in a regression 3D U-net used for radiation dose prediction is presented. READ MORE
