Sökning: "model estimation"

Visar resultat 11 - 15 av 1639 uppsatser innehållade orden model estimation.

1. 11. Regularization Methods and High Dimensional Data: A Comparative Study Based on Frequentist and Bayesian Methods

   Kandidat-uppsats, Lunds universitet/Statistiska institutionen

   Författare :Markus Gerholm; Johan Sörstadius; [2024]
   Nyckelord :Linear regression; high dimensional data; regularization; Bayesian methods; Mathematics and Statistics;

   Sammanfattning : As the amount of high dimensional data becomes increasingly accessible and common, the need for reliable methods to combat problems such as overfitting and multicollinearity increases. Models need to be able to manage large data sets where predictor variables often outnumber the amount of observations. LÄS MER

3. 12. MODELLING THE SMOLT PRODUCTIVITY OF BROWN TROUT (SALMO TRUTTA) IN HAGA Å

   Kandidat-uppsats, Göteborgs universitet / Instiutionen för biologi och miljövetenskap

   Författare :Lukas Almgren; [2023-10-30]
   Nyckelord :Brown trout; Salmo trutta; Trout habitat score; THS; Haga å; electro-fishing survey;

   Sammanfattning : The brown trout (Salmo trutta) is a facultatively anadromous species, some individuals migrate from the rearing environment in the rivers to the sea while other individuals stay in fresh water. To determine the suitability of a stream for juvenile trout the organization SGBALANST has developed what is called the "Trout habitat score" (THS) model. LÄS MER

4. 13. Value at Risk Estimation using GARCH Family Models: A Comparison of Different Specifications and Distributions.

   Kandidat-uppsats, Göteborgs universitet/Institutionen för nationalekonomi med statistik

   Författare :Khaled Jrideh; [2023-05-26]
   Nyckelord :;

   Sammanfattning : 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. LÄS MER

5. 14. Heart rate estimation from wrist-PPG signals in activity by deep learning methods

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Marie-Ange Stefanos; [2023]
   Nyckelord :Deep Learning; Medical Data; Signal Processing; Heart Rate Estimation; Wrist Photoplethysmography; Djup lärning; Medicinska Data; Signalbehandling; Pulsuppskattning; Handledsfotopletysmograf;

   Sammanfattning : In the context of health improving, the measurement of vital parameters such as heart rate (HR) can provide solutions for health monitoring, prevention and screening for certain chronic diseases. Among the different technologies for HR measuring, photoplethysmography (PPG) technique embedded in smart watches is the most commonly used in the field of consumer electronics since it is comfortable and does not require any user intervention. LÄS MER

7. 15. Uncertainty Estimation in Radiation Dose Prediction U-Net

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Frida Skarf; [2023]
   Nyckelord :Radiation dose prediction models; U-net; quantile regression; Monte Carlo Dropout; epistemic uncertainty estimation; aleatoric uncertainty estimation; Stråldospredicerande modeller; U-net; kvantilregression; Monte Carlo Dropout; epistemisk osäkerhetsskattning; aletorisk osäkerhetsskattning;

   Sammanfattning : 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. LÄS MER