Blar i NTNU Open på forfatter "Næss, Arvid"
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A comparative study of the stochastic averaging method and the path integration method for nonlinear ship roll motion in random beam seas
Chai, Wei; Dostal, Leo; Næss, Arvid; Leira, Bernt Johan (Journal article; Peer reviewed, 2017)In this paper, the energy-based stochastic averaging method and the path integration method are applied to study the stochastic response of the nonlinear roll motion in random beam seas. Specifically, the Markov diffusion ... -
An Application of the ACER Method to Norwegian Water Level Data: A Comparison of Return Level Estimates
Skjong, Morten (Master thesis, 2011)In this Master's thesis we have used data from eight different locations in Norway to estimate the distributions of extreme water levels. The locations used are Oslo, Heimsjø, Honningsvåg, Narvik, Harstad, Tregde, Andenes ... -
an extreme value perspective on the nordic electricity maket spot price extreme changes
Zhou, Yan (Master thesis, 2010)We explore the nordic electricity maket spot price extreme changes by using an extreme value perspective based on Nord pool. P.S Sorry I really dont know how to use this system, it makes submission of master paper complicated ... -
Analysis of Bivariate Extreme Values
Egeland Busuttil, Chris (Master thesis, 2015)Results show that there is high agreement between the distribution of the bivariate ACER functions and the distribution of the copula models with ACER marginals for all time series. The distribution of the copula models ... -
Aspects of Applying the ACER Method to Ocean Wave Data
Valberg, Morten (Master thesis, 2010)This thesis gives a presentation of the classical Peaks Over Threshold (POT) method and the recently developed Average Conditional Exceedence Rates (ACER) method. Real life ocean significant wave height data sets, each ... -
Comparative Study of the Path Integration Method and the Stochastic Averaging Method for Nonlinear Roll Motion in Random Beam Seas
Chai, Wei; Dostal, Leo; Næss, Arvid; Leira, Bernt Johan (Journal article; Peer reviewed, 2017)In this work, the path integration method and the energy-based stochastic averaging method are introduced in order to study the stochastic responses of ship roll motion in random beam seas. Based on the Markov property of ... -
Comparing the ACER and POT MCMC Extreme Value Statistics Methods Through Analysis of Commodities Data
Rødvei, Kristoffer Kofoed (Master thesis, 2016)The Average Conditional Exceedance Rate and Peak Over Threshold Markov Chain Monte Carlo are two extreme value statistical methods, compared in this work. They are tested for both extrapolations and prediction intervals. ... -
Comparision of methods and software tools for availability assessment of production systems
Vesteraas, Astrid Hetland (Master thesis, 2008)This thesis presents and considers several different methods for computation of availability and production availability for production system. It is assumed that the system handles flow of a fluid. The thesis presents two ... -
Comparison of ACER and POT Methods for estimation of Extreme Values
Dahlen, Kai Erik (Master thesis, 2010)Comparison of the performance of the ACER and POT methods for prediction of extreme values from heavy tailed distributions. To be able to apply the ACER method to heavy tailed data the ACER method was first modified to ... -
Current profile analysis and extreme value prediction in the LH11-1 oil field of the South China Sea based on prototype monitoring
Liu, Ming; Wu, Wenhua; Tang, Da; Ma, Hongyan; Næss, Arvid (Journal article; Peer reviewed, 2018)Current is a key ocean-environmental factor and exhibits strong non-stationary random characteristics. The complexities of current modeling present significant challenges for deep sea oil exploitation. The multiyear return ... -
Estimation and Comparison of "Value atRisk" of crude oil prices using HistoricalSimulation, GARCH and GPD methods
Malik, Abdul Ghaffar Rehman (Master thesis, 2017)My results indicate that conditional Extreme Value Theory and Filtered Historical Simulation procedures offer a major improvement over the traditional methods (non-parametric and parametric). Such models produce a VaR which ... -
Estimation of Extreme Values by the Average Conditional Exceedance Rate Method
Næss, Arvid; Gaidai, Oleg; Karpa, Oleh Ihorovych (Journal article; Peer reviewed, 2013)This paper details a method for extreme value prediction on the basis of a sampled time series. The method is specifically designed to account for statistical dependence between the sampled data points in a precise manner. ... -
Estimation of Reliability by Monte Carlo Simulations: Combined with Optimized Parametric Models
Bø, Harald Svandal (Master thesis, 2014)A new method for efficient Monte Carlo simulations is developed, and used to estimate the reliability of dependent and independent systems. The method consists of parametrized Monte Carlo simulations, where the robust ... -
Extreme Value Analysis & Application of the ACER Method on Electricity Prices
Anda, Torgeir (Master thesis, 2012)In this thesis we have explored the very high prices that sometimes occurs in the Nord Pool electricity market Elspot. By applying AR-GARCH time series models, extreme value theory, and ACER estimation techniques, we have ... -
Fast pricing of barrier options with NIG dynamics
Aukrust, Eivind Grøver (Master thesis, 2008)We show how we can price different barrier options very fast and accurately using numerical path integration. We will assume the underlying stock follow a NIG process. -
Global Buckling Reliability Analysis of Slender Network Arch Bridges: An Application of Monte Carlo-Based Estimation by Optimized Fitting
Rønnquist, Anders; Næss, Arvid (Chapter, 2017)Network arch bridges are extremely slender bridge structures with a very efficient 16 load-carrying structure. This configuration can carry loads that are several times greater 17 than traditional tied-arch bridges with ... -
Lévy Processes and Path Integral Methods with Applications in the Energy Markets
Oshaug, Christian A. J. (Master thesis, 2011)The objective of this thesis was to explore methods for valuation of derivatives in energy markets. One aim was to determine whether the Normal inverse Gaussian distributions would be better suited for modelling energy ... -
Long-term extreme response and reliability of a vessel rolling in random beam seas
Chai, Wei; Næss, Arvid; Leira, Bernt Johan (Journal article; Peer reviewed, 2018)In this paper, the long-term extreme response of a vessel rolling in random beam seas and the associated reliability evaluation are addressed. The long-term response analysis is based on the upcrossing rates of the roll ... -
Methods for Extreme Value Statistics Based on Measured Time Series
Haug, Even (Master thesis, 2008)The thesis describes the Average Exceedance Rate (AER) method, which is a method for predicting return levels from sampled time series. The AER method is an alternative to the Peaks over threshold (POT) method, which is ... -
Modeling and Calibration of Electricity Price Dynamics for Derivatives Valuation
Nybakk, Ewa (Master thesis, 2013)The objective of this thesis is to model electricity price dynamics and use the results to valuate derivatives. Electricity prices are known to display features such as spikes, seasonality and jumps, leading to large ...