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Computer simulation is now increasingly being used for design and performance evaluation of communication systems. When simulating a mobile wireless channel for communication systems, it is usually assumed that the fading process is a random variate with Rayleigh distribution. The random variates of the fading process should also have other properties, like autocorrelation, spectrum, etc. At present, there are a number of methods to generate the Rayleigh fading process, some of them quite recently proposed. Due to the use of different Rayleigh fading generators, different simulations of the same communication system yield different results. Three methods, viz., the Jakes method, the IDFT method and the filtering WGN method, have been studied, simulated and compared based on the Rayleigh fading process' properties. Various communication systems have been simulated using the Rayleigh fading generators and the difference in the results, if any, have been analyzed. The research studies the different Rayleigh fading generators and compares them using the properties of the Rayleigh fading channel. It is found that the IDFT method and the filtering WGN method generate processes that have properties very close to the ideal Rayleigh fading process.

The thesis considers and examines methods of surface propagation, where the normal velocity of the surface depends on the local curvature and the gradient of the surface. Such fronts occur in many different physical situations from the growth of crystals to the spreading of flames. A number of different methods are considered to find solutions to these physical problems. First the motion is modelled by partial differential equations and numerical methods are developed for solving these equations. The numerical methods involve characteristic, finite differences and transformation of the equations. Stability of the solutions is also briefly considered. Secondly the fronts are modelled by using a cellular approach which subdivides space into regions of small cells. The fronts are assumed to propagate through the region according to stochastic rules. Monte-Carlo simulations are carried out using this approach. Results of the simulations are carried out in two-dimensions and three-dimensions for a number of interesting physical examples.

Nesse trabalho investigamos através de simulações numéricas a evolução da composição genética de uma população, dando atenção especial ao processo dinâmico conhecido como catraca de Muller, que é responsável pela degradação da população devido ao acúmulo de mutações deletérias em populações finitas. Consideramos também a genealogia dos indivíduos em uma população sob a ação da catraca de Muller. Ainda, investigamos analiticamente o limite determinístico do modelo, no qual o tamanho da população é infinito, onde o processo da catraca não atua. O relevo replicativo, ou seja, a função que mapeia a carga genética de um indivíduo com a sua probabilidade de reprodução utilizado nesse trabalho é uma generalização do relevo originalmente proposto por Muller para ilustrar o processo da catraca. Adicionamos a esse relevo um parâmetro de epistase que simula a interação entre os sítios das seqüências dos indivíduos. A escolha desse parâmetro determina três tipos possíveis de epistase: (i) sinergística, no qual as mutações ficam cada vez mais deletérias com o número de mutações já existentes; (ii) atenuante, no qual o efeito deletério de uma nova mutação é atenuado; e (iii) multiplicativa, no qual as novas mutações causam danos idênticos, independentemente do número anterior de mutações / In this work we investigate through numerical simulations the evolution of the genetic composition of a population, giving emphasis to the dynamic process termed Muller\'s ratchet, which is responsible for the degradation of the population due to the accumulation of deleterious mutations in finite populations. We consider also the genealogy of the individuals evolving in a population under the effect of the Muller\'s ratchet. In addition, we investigate analytically the deterministic limit of the model, in which the population size is infinite, where ratchet process does not act. The replication landscape, i.e., the function that maps the genetic load of an individual on its probability of reproduction used in this work is a generalization of that originally considered by Muller to illustrate the process of the ratchet. In particular, we add to that landscape a parameter of epistasis that models the interactions among the sites of the sequences of the individuals. The tunning of this parameter determines three different types of epistasis: (i) synergistic, where the mutations become more deleterious with the number of mutations already present; (ii) diminishing, where the deleterious effect of a new mutation is attenuated; and (iii) multiplicative, where the new mutations cause identical damages, independently of the previous number of mutations

This thesis is composed of two parts. The first parts deals with a technique for pricing American-style contingent options. The second part details a statistical arbitrage model using statistical process control approaches. We propose a novel simulation approach for pricing American-style contingent claims. We develop an adaptive policy search algorithm for obtaining the optimal policy in exercising an American-style option. The option price is first obtained by estimating the optimal option exercising policy and then evaluating the option with the estimated policy through simulation. Both high-biased and low-biased estimators of the option price are obtained. We show that the proposed algorithm leads to convergence to the true optimal policy with probability one. This policy search algorithm requires little knowledge about the structure of the optimal policy and can be naturally implemented using parallel computing methods. As illustrative examples, computational results on pricing regular American options and American-Asian options are reported and they indicate that our algorithm is faster than certain alternative American option pricing algorithms reported in the literature. Secondly, we investigate arbitrage opportunities arising from continuous monitoring of the price difference of highly correlated assets. By differentiating between two assets, we can separate common macroeconomic factors that influence the asset price movements from an idiosyncratic condition that can be monitored very closely by itself. Since price movements are in line with macroeconomic conditions such as interest rates and economic cycles, we can easily see out of the normal behaviors on the price changes. We apply a statistical process control approach for monitoring time series with the serially correlated data. We use various variance estimators to set up and establish trading strategy thresholds.

This thesis studies the one-factor latent trait model for binary data. In examines the sensitivity of the model when the assumptions about the model are violated, it investigates the information about the prior distribution when the model is estimated semi-parametrically and it also examines the goodness-of-fit of the model using Monte-Carlo simulations. Latent trait models are applied to data arising from psychometric tests, ability tests or attitude surveys. The data are often contaminated by guessing, cheating, unwillingness to give the true answer or gross errors. To study the sensitivity of the model when the data are contaminated we derive the Influence Function of the parameters and the posterior means, a tool developed in the frame of robust statistics theory. We study the behaviour of the Influence Function for changes in the data and also the behaviour of the parameters and the posterior means when the data are artificially contaminated. We further derive the Influence Function of the parameters and the posterior means for changes in the prior distribution and study empirically the behaviour of the model when the prior is a mixture of distributions. Semiparametric estimation involves estimation of the prior together with the item parameters. A new algorithm for fully semiparametric estimation of the model is given. The bootstrap is then used to study the information on the latent distribution than can be extracted from the data when the model is estimated semiparametrically. The use of the usual goodness-of-fit statistics has been hampered for latent trait models because of the sparseness of the tables. We propose the use of Monte-Carlo simulations to derive the empirical distribution of the goodness-of-fit statistics and also the examination of the residuals as they may pinpoint to the sources of bad fit.

No description available.

Nesse trabalho investigamos através de simulações numéricas a evolução da composição genética de uma população, dando atenção especial ao processo dinâmico conhecido como catraca de Muller, que é responsável pela degradação da população devido ao acúmulo de mutações deletérias em populações finitas. Consideramos também a genealogia dos indivíduos em uma população sob a ação da catraca de Muller. Ainda, investigamos analiticamente o limite determinístico do modelo, no qual o tamanho da população é infinito, onde o processo da catraca não atua. O relevo replicativo, ou seja, a função que mapeia a carga genética de um indivíduo com a sua probabilidade de reprodução utilizado nesse trabalho é uma generalização do relevo originalmente proposto por Muller para ilustrar o processo da catraca. Adicionamos a esse relevo um parâmetro de epistase que simula a interação entre os sítios das seqüências dos indivíduos. A escolha desse parâmetro determina três tipos possíveis de epistase: (i) sinergística, no qual as mutações ficam cada vez mais deletérias com o número de mutações já existentes; (ii) atenuante, no qual o efeito deletério de uma nova mutação é atenuado; e (iii) multiplicativa, no qual as novas mutações causam danos idênticos, independentemente do número anterior de mutações / In this work we investigate through numerical simulations the evolution of the genetic composition of a population, giving emphasis to the dynamic process termed Muller\'s ratchet, which is responsible for the degradation of the population due to the accumulation of deleterious mutations in finite populations. We consider also the genealogy of the individuals evolving in a population under the effect of the Muller\'s ratchet. In addition, we investigate analytically the deterministic limit of the model, in which the population size is infinite, where ratchet process does not act. The replication landscape, i.e., the function that maps the genetic load of an individual on its probability of reproduction used in this work is a generalization of that originally considered by Muller to illustrate the process of the ratchet. In particular, we add to that landscape a parameter of epistasis that models the interactions among the sites of the sequences of the individuals. The tunning of this parameter determines three different types of epistasis: (i) synergistic, where the mutations become more deleterious with the number of mutations already present; (ii) diminishing, where the deleterious effect of a new mutation is attenuated; and (iii) multiplicative, where the new mutations cause identical damages, independently of the previous number of mutations

Adsorption processes are widely used for the storage and separation of gases in many industrial and environmental applications. The performance of the process depends strongly on the adsorbent and its interaction with the gases. Therefore, the idea of tailoring the adsorbent to the application by adapting the pore size and/or the chemical composition is very attractive. This work focuses on two groups of customizable hybrid materials: Firstly, in crystalline metal-organic frameworks (MOFs) the chemical and structural properties can be modified by changing the metal-oxide corner or the organic linker. Secondly, periodic mesoporous silica materials can be prepared with different pore sizes and geometries depending on the surfactant and its concentration and additionally modified with organic surface groups. The adsorption behaviour of the materials can be predicted by molecular simulation and thus the influence of modifications can be studied without the need of synthesising the material. For MOFs, the coordinates of the atoms can be obtained from XRD measurements. The quality of the predicted adsorption results was investigated for pure gas (methane, ethane, propane, nitrogen and carbon dioxide) and gas mixture (methane – carbon dioxide) adsorption on the metal-organic framework CuBTC. The comparison showed a good agreement between experimental and simulated results especially at low pressures. In order to create atomistic models for the mesoporous silica structures that are amorphous on the atomistic level, two existing simulation methods to model MCM-41-type materials were combined: micellar structures from coarse grained simulations that capture the phase separation in the surfactant/silica/solvent mixtures were used as input in kinetic Monte Carlo simulation that created the pore model on the atomistic level. The model created with this new methodology showed similar adsorption behaviour compared with a model created only with the kMC method using an ideal geometrical structure as micelle. The influence of modifications of the MOF structures (exchange of metal, linker length/composition and catenation) was investigated by Grand Canonical Monte Carlo simulations for hydrogen adsorption at low temperature and temperature controlled desorption. The peaks in the desorption spectra could be related to steps in the adsorption isotherms at 20 K.

The study seeks to determine the degree of accumulation of Type II error rates, while violating the assumptions of normality, for different specified levels of power among sample means. The study employs a Monte Carlo simulation procedure with three different specified levels of power, methodologies, and population distributions. On the basis of the comparisons of actual and observed error rates, the following conclusions appear to be appropriate. 1. Under the strict criteria for evaluation of the hypotheses, Type II experimentwise error does accumulate at a rate that the probability of accepting at least one null hypothesis in a family of tests, when in theory all of the alternate hypotheses are true, is high, precluding valid tests at the beginning of the study. 2. The Dunn-Bonferroni procedure of setting the critical value based on the beta value per contrast did not significantly reduce the probability of committing a Type II error in a family of tests. 3. The use of an adequate sample size and orthogonal contrasts, or limiting the number of pairwise comparisons to the number of means, is the best method to control for the accumulation of Type II errors. 4. The accumulation of Type II error is irrespective of distributions.