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A Bayesian Analysis of Unobserved Component Models using Ox

Bos, Charles S. - 2011

Estimation of the volatility of time series has taken off since the introduction of the GARCH and stochastic volatility models. While variants of the GARCH model are applied in scores of articles, use of the stochastic volatility model is less widespread. In this articleit is argued that one...

Persistent link: https://www.econbiz.de/10010325752

Solving Discrete Systems of Nonlinear Equations

van der Laan, Gerard; Talman, Dolf; Yang, Zaifu - 2009

prove this we use a simplicial algorithm that terminates with a zero point within a finite number of iterations. The …

Persistent link: https://www.econbiz.de/10010325776

Counting with Combined Splitting and Capture-Recapture Methods

Dupuis, Paul; Kaynar, Bahar; Ridder, Ad; Rubinstein, Reuven - 2011

estimators, and speed of the algorithms. …

Persistent link: https://www.econbiz.de/10010325899

To Bridge, to Warp or to Wrap? A Comparative Study of Monte Carlo Methods for Efficient Evaluation of Marginal Likelihoods

Ardia, David; Hoogerheide, Lennart; van Dijk, Herman K. - 2009

importance sampling or the independence chain Metropolis-Hastings algorithm for posterior analysis. A comparative analysis is …

Persistent link: https://www.econbiz.de/10010325939

Adaptive Mixture of Student-t distributions as a Flexible Candidate Distribution for Efficient Simulation

Ardia, David; Hoogerheide, Lennart F.; van Dijk, Herman K. - 2008

distribution given only a kernel of the target density function. The core algorithm consists in the function AdMit which fits an … the independence chain Metropolis- Hastings algorithm are used to obtain quantities of interest for the target density … the time-consuming and difficult task of tuning a sampling algorithm. The relevance of the package is shown in two …

Persistent link: https://www.econbiz.de/10010326034

Censored Posterior and Predictive Likelihood in Bayesian Left-Tail Prediction for Accurate Value at Risk Estimation

Gatarek, Lukasz; Hoogerheide, Lennart; Hooning, Koen; … - 2013

Accurate prediction of risk measures such as Value at Risk (VaR) and Expected Shortfall (ES) requires precise estimation of the tail of the predictive distribution. Two novel concepts are introduced that offer a specific focus on this part of the predictive density: the censored posterior, a...

Persistent link: https://www.econbiz.de/10010326148

A Class of Adaptive Importance Sampling Weighted EM Algorithms for Efficient and Robust Posterior and Predictive Simulation

Hoogerheide, Lennart; Opschoor, Anne; van Dijk, Herman K. - 2012

A class of adaptive sampling methods is introduced for efficient posterior and predictive simulation. The proposed methods are robust in the sense that they can handle target distributions that exhibit non-elliptical shapes such as multimodality and skewness. The basic method makes use of...

Persistent link: https://www.econbiz.de/10010326223

The R Package MitISEM: Mixture of Student-t Distributions using Importance Sampling Weighted Expectation Maximization for Efficient and Robust Simulation

Basturk, Nalan; Hoogerheide, Lennart; Opschoor, Anne; … - 2012

model parameters and probabilities. The package provides also an extended MitISEM algorithm, 'sequential MitISEM', which … predictive likelihoods. We illustrate the MitISEM algorithm using three canonical statistical and econometric models that are …

Persistent link: https://www.econbiz.de/10010326521

Estimating global migration flow tables using place of birth data

Abel, Guy J. - 2012

A methodology to estimate flow tables of migration transitions for the globe is illustrated in two parts. First, a methodology to derive flows from sequential stock tables is developed. Second, the methodology is applied to recently released World Bank migration stock tables between 1960 and...

Persistent link: https://www.econbiz.de/10010352739

Clustering techniques applied to outlier detection of financial market series using a moving window filtering algorithm

Puigvert Gutiérrez, Josep Maria; Fortiana Gregori, Josep - 2008

In this study we combine clustering techniques with a moving window algorithm in order to filter financial market data … outliers. We apply the algorithm to a set of financial market data which consists of 25 series selected from a larger dataset … of a cluster that represents a different segment of the market. We set up a framework of possible algorithm parameter …

Persistent link: https://www.econbiz.de/10011604994