Arbeitspapier
Some comments on quasi-birth-and-death processes and matrix measures
In this paper we explore the relation between matrix measures and Quasi-Birth-and-Death processes. We derive an integral representation of the transition function in terms of a matrix valued spectral measure and corresponding orthogonal matrix polynomials. We characterize several stochastic properties of Quasi-Birth-and-Death processes by means of this matrix measure and illustrate the theoretical results by several examples.
- Language
-
Englisch
- Bibliographic citation
-
Series: Technical Report ; No. 2008,13
- Subject
-
Block tridiagonal infinitesimal generator
Quasi-Birth-and-Death processes
spectral measure
matrix measure
canonical moments
- Event
-
Geistige Schöpfung
- (who)
-
Dette, Holger
Reuther, Bettina
- Event
-
Veröffentlichung
- (who)
-
Technische Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
- (where)
-
Dortmund
- (when)
-
2008
- Handle
- Last update
-
10.03.2025, 11:41 AM CET
Data provider
This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Arbeitspapier
Associated
- Dette, Holger
- Reuther, Bettina
- Technische Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
Time of origin
- 2008
Other Objects (12)
![Matrix measures, moment spaces and Favard's theorem for the interval [0,1] and [0,∞)](/assets/placeholder/searchResultMediaUnknown.png)
Matrix measures, moment spaces and Favard's theorem for the interval [0,1] and [0,∞)
Matrix Measures, Moment Spaces and Favard's Theorem for the interval [0,1] and [0, infinity)
On robust and efficient designs for risk estimation in epidemiologic studies
Quadrature formulas for matrix measures - a geometric approach
Some comments on specification tests in nonparametric absolutely regular processes
Matrix measures and random walks
Canonical moments, orthogonal polynomials with application to statistics
Strong approximation of eigenvalues of large dimensional Wishart matrices by roots of generalized Laguerre polynomials
A note on the matrix valued q-d algorithm and matrix orthogonal polynomials on [0,1] and [0,∞]
Optimal designs for estimating individual coefficients in Fourier regression models and figures figure 1, figure 2, figure 3 and figure 4
Robust and efficient designs for the Michaelis-Menten model
Constrained D- and D1-optimal designs for polynomial regression
Matrix measures, moment spaces and Favard's theorem for the interval [0,1] and [0,∞)
Matrix Measures, Moment Spaces and Favard's Theorem for the interval [0,1] and [0, infinity)
On robust and efficient designs for risk estimation in epidemiologic studies
Quadrature formulas for matrix measures - a geometric approach
Some comments on specification tests in nonparametric absolutely regular processes
Matrix measures and random walks
Canonical moments, orthogonal polynomials with application to statistics
Strong approximation of eigenvalues of large dimensional Wishart matrices by roots of generalized Laguerre polynomials
A note on the matrix valued q-d algorithm and matrix orthogonal polynomials on [0,1] and [0,∞]
Optimal designs for estimating individual coefficients in Fourier regression models and figures figure 1, figure 2, figure 3 and figure 4
Robust and efficient designs for the Michaelis-Menten model
Constrained D- and D1-optimal designs for polynomial regression
Matrix measures, moment spaces and Favard's theorem for the interval [0,1] and [0,∞)
Matrix Measures, Moment Spaces and Favard's Theorem for the interval [0,1] and [0, infinity)
On robust and efficient designs for risk estimation in epidemiologic studies
Quadrature formulas for matrix measures - a geometric approach
Some comments on specification tests in nonparametric absolutely regular processes
Matrix measures and random walks
Canonical moments, orthogonal polynomials with application to statistics
Strong approximation of eigenvalues of large dimensional Wishart matrices by roots of generalized Laguerre polynomials
A note on the matrix valued q-d algorithm and matrix orthogonal polynomials on [0,1] and [0,∞]
Optimal designs for estimating individual coefficients in Fourier regression models and figures figure 1, figure 2, figure 3 and figure 4
Robust and efficient designs for the Michaelis-Menten model