The main focus of this thesis is to develop full parametric and semiparametric Bayesian inference for data arising from triangular distributions. A natural consequence of working with such distributions is it allows one to consider regression models where the response variable is now the mode of the data distribution. A new family of nonparametric prior distributions is developed for a certain class of convex densities of particular relevance to mode regressions. Triangular distributions arise in several contexts such as geosciences, econometrics, finance, health care management, sociology, reliability engineering, decision and risk analysis, etc. In many fields, experts, typically, have a reasonable idea about the range and most likely values that define a data distribution. Eliciting these quantities is thus, generally, easier than eliciting moments of other commonly known distributions. Using simulated and actual data, applications of triangular distributions, with and without mode regressions, in some of the aforementioned areas are tackled. / text

This investigation is designed to find the net rate of decrease in the component of velocity parallel to the original direction of motion of a proton moving through an electron gas exhibiting a non-spherical velocity distribution.

This paper discusses results of a computer simulation to investigate several different tests when sampling several distributions. The hypothesis H0: μ=0 was tested against H0: μ≠0, using the usual t-test, trimmed t-test, the Jackkinfe, the Boostrap and signed-rank test. The p-values and empirical power show that the Bootstrap is as good as the t-test. The Jackknife procedure is too liberal, always obtaining small p-values. The signed-rank is a fairly good test if the data follows the Cauchy Distribution.

The LHC, with its center-of-mass energy of 7 TeV, offers the chance to investigate the fundamental constituents of matter at a higher energy scale than ever before. Using the data acquired by the ATLAS detector in the summer of 2010, two different measures of the angular distributions of dijet final states are studied and compared to Standard Model QCD expectations. Such a comparison is used to set new stringent limits on the existence of quark substructure.

The LHC, with its center-of-mass energy of 7 TeV, offers the chance to investigate the fundamental constituents of matter at a higher energy scale than ever before. Using the data acquired by the ATLAS detector in the summer of 2010, two different measures of the angular distributions of dijet final states are studied and compared to Standard Model QCD expectations. Such a comparison is used to set new stringent limits on the existence of quark substructure.

No description available.

We use inequalities to design short universal algorithms that can be used to generate random variates from large classes of univariate continuous or discrete distributions (including all log-concave distributions). The expected time is uniformly bounded over all these distributions. The algorithms can be implemented in a few lines of high level language code. In opposition to other black-box algorithms hardly any setup step is required and thus it is superior in the changing parameter case. (author's abstract) / Series: Preprint Series / Department of Applied Statistics and Data Processing

Infinitely divisible distributions and processes have been the object of extensive research not only from the theoretical point of view but also for practical use, for example, in queueing theory or mathematical finance. In this thesis, we will study some of their subclasses with a view towards financial modeling. As generalizations of stable distributions, we study the tempered stable distributions and introduce the new classes of layered stable distributions as well as the mixed stable distributions, along with the corresponding Levy processes. As a further generalization of infinitely divisible processes, fractional tempered stable motions are defined. These theoretical studies will be complemented by some more practical ones, such as the simulation of sample paths, parameter estimations, financial portfolio hedging, and solving stochastic differential equations.

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The objective of this thesis is to provide the modeling procedure for a tubular permanent magnet generator with Halbach array. The cylindrical-coordinated magnetic flux distributions generated by the stator winding currents and permanent magnets can be realized by deriving the magnetic vector potential in Bessel form from the Maxwell's equations. Then, the functional expressions of inductance matrix and magnetic flux linkage can be obtained. The detailed mathematic model of the proposed system combined with the actual operational properties can be further established and implemented by using the Matlab/Simulink software. The applicability of such mathematic model is also confirmed with experimental results.