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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Über die Unfallflucht als Straftat : eine kritische Untersuchung zum Zusammenhang der Strafbarkeit der Unfallflucht mit den Besonderheiten des Straßenverkehrs /

Steenbock, Maike. January 2004 (has links) (PDF)
Univ., Diss.--Hamburg, 2003. / Literaturverz. S. 203 - 219.
2

Automatic Markov Chain Monte Carlo Procedures for Sampling from Multivariate Distributions

Karawatzki, Roman, Leydold, Josef, Pötzelberger, Klaus January 2005 (has links) (PDF)
Generating samples from multivariate distributions efficiently is an important task in Monte Carlo integration and many other stochastic simulation problems. Markov chain Monte Carlo has been shown to be very efficient compared to "conventional methods", especially when many dimensions are involved. In this article we propose a Hit-and-Run sampler in combination with the Ratio-of-Uniforms method. We show that it is well suited for an algorithm to generate points from quite arbitrary distributions, which include all log-concave distributions. The algorithm works automatically in the sense that only the mode (or an approximation of it) and an oracle is required, i.e., a subroutine that returns the value of the density function at any point x. We show that the number of evaluations of the density increases slowly with dimension. An implementation of these algorithms in C is available from the <a href="http://statmath.wu-wien.ac.at/software/hitro/">authors</a>. (author's abstract) / Series: Research Report Series / Department of Statistics and Mathematics
3

Automatic Markov Chain Monte Carlo Procedures for Sampling from Multivariate Distributions

Karawatzki, Roman, Leydold, Josef January 2005 (has links) (PDF)
Generating samples from multivariate distributions efficiently is an important task in Monte Carlo integration and many other stochastic simulation problems. Markov chain Monte Carlo has been shown to be very efficient compared to "conventional methods", especially when many dimensions are involved. In this article we propose a Hit-and-Run sampler in combination with the Ratio-of-Uniforms method. We show that it is well suited for an algorithm to generate points from quite arbitrary distributions, which include all log-concave distributions. The algorithm works automatically in the sense that only the mode (or an approximation of it) and an oracle is required, i.e., a subroutine that returns the value of the density function at any point x. We show that the number of evaluations of the density increases slowly with dimension. (author's abstract) / Series: Preprint Series / Department of Applied Statistics and Data Processing
4

Vägen till 2.0 : Att hantera en allvarlig hjärnskada / The journey to 2.0 : Coping with a serious brain injury

Blom, Malin January 2018 (has links)
Mitt masterprojekt är en bok som syftar till att stötta anhöriga till personer med förvärvad hjärnskada, där jag använder mig själv och min egen rehabilitering efter en smitningsolycka som fallstudie. / My master project is a book that aims to support relatives of people with aquired brain injuries, where I use myself and my own rehabilitetion after a hit-and-run accident as a case study.

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