National Repository of Grey Literature 11 records found  1 - 10next  jump to record: Search took 0.00 seconds. 
Stochastic Calculus and Its Applications in Biomedical Practice
Klimešová, Marie ; Růžičková, Miroslava (referee) ; Dzhalladova, Irada (referee) ; Baštinec, Jaromír (advisor)
V předložené práci je definována stochastická diferenciální rovnice a jsou uvedeny její základní vlastnosti. Stochastické diferenciální rovnice se používají k popisu fyzikálních jevů, které jsou ovlivněny i náhodnými vlivy. Řešením stochastického modelu je náhodný proces. Cílem analýzy náhodných procesů je konstrukce vhodného modelu, který umožní porozumět mechanismům, na jejichž základech jsou generována sledovaná data. Znalost modelu také umožňuje předvídání budoucnosti a je tak možné kontrolovat a optimalizovat činnost daného systému. V práci je nejdříve definován pravděpodobnostní prostor a Wienerův proces. Na tomto základě je definována stochastická diferenciální rovnice a jsou uvedeny její základní vlastnosti. Závěrečná část práce obsahuje příklad ilustrující použití stochastických diferenciálních rovnic v praxi.
Generalized Moran process
Svoboda, Jakub ; Šámal, Robert (advisor) ; Balko, Martin (referee)
The Moran process is a model for simulating evolutionary dynamics. In that model, one mutant with higher fitness is introduced to a structured population. Evolution is simulated in rounds. In one round, individual is selected proportio- nally to its fitness and spreads to the place of a random neighbour. In this thesis, we motivate the Moran process, present basic results, and define our variant. We work in a vertex dependent model; every individual has fitness according to its type and occupied vertex. In the vertex dependent model we prove two theorems about the number of steps the process has to make to get to the stable state. We show that on the complete graph, the process takes only polynomially many steps and we find a graph where the process take exponentially many steps, but in the normal settings the number of steps is the same as on the complete graph. 1
Autoregressive models
Rathouský, Marek ; Zichová, Jitka (advisor) ; Prášková, Zuzana (referee)
The purpose of this thesis is to compare the classic autoregressive model of order 1 to integer autoregressive model of order 1. Considering the popularity of AR(1) model, only the basics are covered within this thesis. The main focus is on the INAR(1) model. Operator ◦ necessary for INAR(1) definition is intro- duced alongside with its properties with proof. All of the non-trivial properties of INAR(1) are followed by detailed proof, stationarity condition is also derived. Common estimation techniques are described for poisson INAR(1) model. This thesis also contains simulation study, which focuses on the rate of convergence of estimates of parameters. 1
Stochastic methods in portfolio management
Kobulnická, Ivana ; Radová, Jarmila (advisor) ; Diviš, Martin (referee)
This master thesis aims to describe and apply in practice solutions of basic tasks in portfolio management- portfolio optimization, portfolio modelling and risk management. As value of financial assets in future is a random variable, it is necessary to use mathematic tools resulting from probability theory and statistics. Basic terms from this area are for example stochastic Wiener process or geometric Brownian motion, which are described in first part of this thesis. Next parts of thesis describe the Markowitz model or method Value at Risk. In the last part of thesis is application of calculation VaR using Monte Carlo simulation for stock portfolio constructed as optimal portfolio according to Markowitz model from real data.
Roulette and its strategies
Zadražil, Tomáš ; Staněk, Jakub (advisor) ; Slavík, Antonín (referee)
Objective of this thesis is to describe history of gambling, in a context of roulette to explain basic and advanced parts of probability theory which allow to the reader to decide about function of several popular roulette systems. There was mainly used expected value of discrete random variable, homogenous discrete-time Markov chain and simulations made in programming language R. Concrete output of the thesis are in precisely calculated expected values of a profit with fixed spins and with chosen limitation and corresponding estimations provided by simulation. On the basis of that it's possible to decide which systems are functional and which are not. Main contribution of this text is in didactical approach which helps to describe popular problematics of roulette systems by using basic and advanced areas of probability theory.
Testing time-series characteristics of prices of financial derivatives
Vdovičenko, Martin ; Kadavý, Matěj (advisor) ; Šnupárková, Jana (referee)
This work discusses Brownian motion and its basic transformations. The work describes basic properties of its trajectories and shows that Brownian motion is a martingale and a self-similar process. Next, we discuss time series analysis. We introduce graphical tools for analyzing data and we describe theoretical basics of some normality and independence tests. Finally, we consider the hypothesis that in the short run the price of financial assets can be modelled by Brownian motion. We conduct basic statistical tests on real data using the R progam and we talk through our results.
A Software Tool for Analyzing Stochastic Data
Lipták, Juraj ; Peringer, Petr (referee) ; Hrubý, Martin (advisor)
This thesis discusses the possibility of modeling stochastic processes. Elements of the system with the source of randomness in some cases may be represented by probability distribution. The reader will be acquainted with methods of statistical induction for selecting suitable distribution and generating random numbers. Tool developed in this project aims to propose appropriate probability distribution based on empirical data and provide random variable generating with proposed distribution.
Models of Queueing Systems
Horký, Miroslav ; Dvořák, Jiří (referee) ; Šeda, Miloš (advisor)
The master’s thesis solves models of queueing systems, which use the property of Markov chains. The queueing system is a system, where the objects enter into this system in random moments and require the service. This thesis solves specifically such models of queueing systems, in which the intervals between the objects incomings and service time have exponential distribution. In the theoretical part of the master’s thesis I deal with the topics stochastic process, queueing theory, classification of models and description of the models having Markovian property. In the practical part I describe realization and function of the program, which solves simulation of chosen model M/M/m. At the end I compare results which were calculated in analytic way and by simulation of the model M/M/m.
Queueing theory utilization in packet network design and optimization process
Rýzner, Zdeněk ; Zeman, Václav (referee) ; Novotný, Vít (advisor)
This master's thesis deals with queueing theory and its application in designing node models in packet-switched network. There are described general principles of designing queueing theory models and its mathematical background. Further simulator of packet delay in network was created. This application implements two described models - M/M/1 and M/G/1. Application can be used for simulating network nodes and obtaining basic network characteristics like packet delay or packet loss. Next, lab exercise was created, in that exercise students familiarize themselves with basic concepts of queueing theory and examine both analytical and simulation approach to solving queueing systems.
Non-negative linear operators and their use in econometric and statistic models
Horský, Richard ; Arlt, Josef (advisor) ; Vrabec, Michal (referee) ; Klazar, Martin (referee)
Non-negative operators, in special case non-negative matrices, are an interesting topics for many scientists and scientific teams from the beginning of the 20th century. It is not suprising because there are a lot of applications in different areas of science like economy, statistics, linear programming, computer science and others. We can give as the particular example the theory of the Markov chains in which we deal with non-negative matrices, so called transition matrices. They are of the special form and we called them stochastic matrices. Another example is given by the non-negative operator on spaces of infinite dimension which is employed in the theory of stochastic processes. It is the backward shift operator called the lag operator as well. The non-negativity in these examples is considered as the piecewise non-negativity. Another type of non-negativity is that in the sense of inner products. In the case of matrices we talk about positive-definite or positive-semidefinite matrices. A typical example is the covariance matrix of a random vector or symmetrization of any linear operator, for instance the symmetrization of the difference operator. The terms inverse problem or ill-posed problem have been gaining popularity in modern science since the middle of the last century. The subjects of the first publications in this area were related to quantum scattering theory, geophysics, astronomy and others. Thanks to powerful computers the chances for applications of the theory of inverse and ill-posed problems has extended in almost all fields of science which use mathematical methods. Ill-posed problems bear the feature of instability and there is the need of regularization if we want to get some reasonable solution. A typical example of the regularization is the differencing of stochastic process with the purpose to obtain a stationary process. Another concept of regularization used for solving e.g. integral equations with compact operators consists in application of regularization method as truncated singular value decomposition, Tichonov regularization method or Landweber iteration method. Mathematical tools employed in this work are those of the functional analysis. It is the area of mathematics in which distinct mathematical structures meet each other. They are structures built within different mathematical disciplines as mathematical analysis, topology, theory of sets, algebra (mainly linear algebra) and theory of measure (probability). The functional analysis framework enables us to obtain right formulations of definitions and problems providing the general view on the notions and problems of the theory of stochastic processes.

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