Generiranje naključnih spremenljivk

diplomsko delo

Aneta Ančev (Author), Dominik Benkovič (Mentor)

Abstract

Diplomsko delo obravnava generiranje naključnih spremenljivk. V uvodnem poglavju so naštete definicije in porazdelitve iz teorije verjetnosti, ki jih potrebujemo v nadaljevanju diplomskega dela. Predstavljeno je generiranje psevdonaključnih števil, ki je osnova za generiranje naključnih spremenljivk. Psevdonaključna števila so vrednosti enakomerno porazdeljene naključne spremenljivke na intervalu (0,1). Metode generiranja so obravnavne ločeno glede na to, ali je spremenljivka diskretno ali zvezno porazdeljena. Spoznamo metodo inverzne transformacije. Navedena sta tudi algoritma za generiranje binomsko porazdeljene naključne spremenljivke in spremenljivke, porazdeljene po Poissonovem zakonu. Predstavljena je tudi metoda zavrnitve. V nadaljevanju sta predstavljeni že navedeni metodi za generiranje zveznih naključnih spremenljivk in tudi polarna metoda za generiranje normalno porazdeljenih naključnih spremenljivk. Na koncu obravnavamo generiranje Poissonovega procesa.

Keywords

matematika;naključne spremenljivke;naključna števila;transformacija;inverzija;zavrnitev;polarna metoda;Poissonov proces;diplomska dela;

Data

Language:	Slovenian
Year of publishing:	2011
Source:	Maribor
Typology:	2.11 - Undergraduate Thesis
Organization:	UM FNM - Faculty of Natural Sciences and Mathematics
Publisher:	[A. Ančev]
UDC:	51(043.2)
COBISS:	18753800
Views:	2300
Downloads:	188
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	English
Secondary title:	GENERATING RANDOM VARIABLES
Secondary abstract:	The graduation thesis focuses on generating random variables. In the introduction chapter we introduce some definitions and imporant distributions of probability theory which are needed in the following chapters of the graduation thesis. Generating of pseudo-random numbers is described, which are the base for generating random variables. A pseudo-random number is the value of a uniformly distributed random variable on the interval (0,1). The generating methods are described separately, according to the variable, which can be distributed discete or continuous. We also get familiar with the inverse transform method. The algorithm for generating binomically distributed random variables as well as the variables distributed according to the Poisson law is introduced. In addition, the rejection method is also presented. The following chapters descibe the methods of generating continuous random variables and also the polar method for generating normal random variables. Finally, generating of the Poisson process is discussed.
Secondary keywords:	random variable;random number;the inverse transform method;the rejection method;the polar method;Poisson process;
URN:	URN:SI:UM:
Type (COBISS):	Undergraduate thesis
Thesis comment:	Univ. v Mariboru, Fak. za naravoslovje in matematiko, Oddelek za matematiko in računalništvo
Pages:	61 f.
Keywords (UDC):	mathematics;natural sciences;naravoslovne vede;matematika;mathematics;matematika;
ID:	8762030