Search Results - subject:"Rotation matrix"

Ledermann, Daniel - Henley Business School, University of Reading - 2011

This paper explores the properties of random orthogonal matrix (ROM) simulation when the random matrix is drawn from the class of rotational matrices. We describe the characteristics of ROM simulated samples that are generated using random Hessenberg, Cayley and exponential matrices and compare...

Persistent link: https://www.econbiz.de/10011206321

Independent component analysis via copula techniques

Chen, Ray-Bing; Guo, Meihui; Härdle, Wolfgang Karl; … - 2008

Independent component analysis (ICA) is a modern factor analysis tool developed in the last two decades. Given p-dimensional data, we search for that linear combination of data which creates (almost) independent components. Here copulae are used to model the p-dimensional data and then...

Persistent link: https://www.econbiz.de/10010274138

Independent Component Analysis Via Copula Techniques

Chen, Ray-Bing; Guo, Meihui; Härdle, Wolfgang; Huang, … - Sonderforschungsbereich 649: Ökonomisches Risiko, … - 2008

(flij) is a p-dimensional Givens rotation matrix which represents a rotation in the plan spanned by the axes xi and xj, i < j …=2. 3. Choose d copulae and deflne the objective function, O( 1;:::; d). 4. Apply SA algorithm to flnd the rotation matrix R … the advantages of this method. Key words: Blind source separation, Canonical maximum likelihood method, Givens rotation …

Persistent link: https://www.econbiz.de/10005677950

No-Arbitrage ROM simulation

Geyer, Alois; Hanke, Michael; Weissensteiner, Alex - In: Journal of Economic Dynamics and Control 45 (2014) C, pp. 66-79

Ledermann et al. (2011) propose random orthogonal matrix (ROM) simulation for generating multivariate samples matching means and covariances exactly. Its computational efficiency compared to standard Monte Carlo methods makes it an interesting alternative. In this paper we enhance this method׳s...

Persistent link: https://www.econbiz.de/10011051879

No-Arbitrage ROM simulation

Geyer, Alois; Hanke, Michael; Weissensteiner, Alex - In: Journal of economic dynamics & control 45 (2014), pp. 66-79

Persistent link: https://www.econbiz.de/10010474462

Further properties of random orthogonal matrix simulation

Ledermann, Daniel; Alexander, Carol - In: Mathematics and Computers in Simulation (MATCOM) 83 (2012) C, pp. 56-79

Random orthogonal matrix (ROM) simulation is a very fast procedure for generating multivariate random samples that always have exactly the same mean, covariance and Mardia multivariate skewness and kurtosis. This paper investigates how the properties of parametric, data-specific and...

Persistent link: https://www.econbiz.de/10010870086

Generation of three-dimensional random rotations in fitting and matching problems

Habeck, Michael - In: Computational Statistics 24 (2009) 4, pp. 719-731

Persistent link: https://www.econbiz.de/10008467047