Essays about: "Monte Carlo Approximation"

Showing result 1 - 5 of 62 essays containing the words Monte Carlo Approximation.

  1. 1. Branching Out with Mixtures: Phylogenetic Inference That’s Not Afraid of a Little Uncertainty

    University essay from KTH/Matematisk statistik

    Author : Ricky Molén; [2023]
    Keywords : Phylogeny; Bayesian analysis; Markov chain Monte Carlo; Variational inference; Mixture of proposal distributions; Fylogeni; Bayesiansk analys; Markov Chain Monte Carlo; Variationsinferens; Mixturer av förslagsfördelningar;

    Abstract : Phylogeny, the study of evolutionary relationships among species and other taxa, plays a crucial role in understanding the history of life. Bayesian analysis using Markov chain Monte Carlo (MCMC) is a widely used approach for inferring phylogenetic trees, but it suffers from slow convergence in higher dimensions and is slow to converge. READ MORE

  2. 2. Multi-factor approximation : An analysis and comparison ofMichael Pykhtin's paper “Multifactor adjustment”

    University essay from Umeå universitet/Institutionen för matematik och matematisk statistik

    Author : Michael Zanetti; Philip Güzel; [2023]
    Keywords : Credit risk; Value at Risk; Expected Shortfall; Monte Carlo simulation; Advanced Internal Rantings-Based models; Kreditrisk; Value at Risk; Expected Shortfall; Monte Carlo simulation; Advanced Internal Rantings-Based-modeller;

    Abstract : The need to account for potential losses in rare events is of utmost importance for corporations operating in the financial sector. Common measurements for potential losses are Value at Risk and Expected Shortfall. These are measures of which the computation typically requires immense Monte Carlo simulations. READ MORE

  3. 3. When is Electric Freight Cost Competitive? : Computational modeling and simulation of total cost of ownership for electric truck fleets

    University essay from Linköpings universitet/Institutionen för ekonomisk och industriell utveckling

    Author : Anton Zackrisson; [2023]
    Keywords : electric freight; battery-electric trucks; total cost of ownership; decision making under deep uncertainty DMDU ; cost-competitiveness; exploratory modeling and analysis EMA ; EMA workbench; quasi-Monte Carlo method; VRP; EVRP; elektrifiering; godstransport; elektriska lastbilar; total ägandekostnad; kostnadskonkurrenskraft; ruttoptimering;

    Abstract : Battery electric trucks (BETs) offer environmental benefits in terms of reduced carbon emissions and enhanced energy efficiency but have been challenged with economic viability compared to conventional internal combustion engine trucks (ICETs) caused by substantial acquisition costs, limited charging infrastructure, and concerns regarding range and payload capacity.  Previous studies focus on TCO at the vehicle or policy level but overlook the system and firm-level impacts. READ MORE

  4. 4. Anomaly or not Anomaly, that is the Question of Uncertainty : Investigating the relation between model uncertainty and anomalies using a recurrent autoencoder approach to market time series

    University essay from Umeå universitet/Institutionen för datavetenskap

    Author : Anton Vidmark; [2022]
    Keywords : Uncertainty in deep learning; Bayesian; anomaly detection; novelty detection; stock market; time series;

    Abstract : Knowing when one does not know is crucial in decision making. By estimating uncertainties humans can recognize novelty both by intuition and reason, but most AI systems lack this self-reflective ability. In anomaly detection, a common approach is to train a model to learn the distinction between some notion of normal and some notion of anomalies. READ MORE

  5. 5. Uncertainty quantification for neural network predictions

    University essay from Umeå universitet/Statistik

    Author : Jonas Borgström; [2022]
    Keywords : ;

    Abstract : Since their inception, machine learning methods have proven useful, and their usability continues to grow as new methods are introduced. However, as these methods are used for decision-making in most fields, such as weather forecasting,medicine, and stock market prediction, their reliability must be appropriately evaluated before the models are deployed. READ MORE