No description available.

This study investigates the main factors of production, their interaction and influence on cycle time efficiency for shovel-truck systems on surface mines. The main factors are truck payload, cycle time and operator proficiency. It is now routine that shoveltruck cycles are analysed using simulation methods. The Elbrond, FPC, Talpac, Arena and Machine Repair simulation models are discussed to explain how their model characteristics contribute to the differences in their reported cycle efficiency as indicated by productivity results. The Machine Repair Model based on Markov chains is adapted for shovel-truck systems and examined for calculating shovel-truck cycle times. The various probability distributions that can be use to model particular cycle time variables and some methods in selecting the “best” fit are examined. Truck cycle time variable sensitivity is examined by using the Excel® add-on program @Risk (Palisade Corp.) in determining their respective weighting or contribution within the total cycle time variability. The analysis of cycle efficiency leads ultimately to sizing of a shovel-truck system. When determining a fleet size for a particular surface operation the planning engineers will tend to use one and to a lesser extent perhaps two separate simulation models. This study calculates the productivity (tonnes per hour) for a “virtual mine” with a variable number of trucks, variable cycle distances and variable truck loading times. The study also includes a separate analysis of cycle time variables and their probability distributions for the Orapa diamond mine in Botswana, to show possible distributions for various cycle variables. The study concludes with a calculation of the truck fleet size using the Elbrond, FPC, Talpac and Arena and Machine Repair models for the Optimum Colliery coal mine and then compares the results and their correlation. The main findings are that the calculation of waiting time is different for the various models, each model yields a unique fleet sizing solution and any solution in effect represents a range of results.

The diploma thesis deals with a theoretical description and practical use of probit analysis, which is a part of survival analysis. The thesis shows different probit models, their differences and appropriateness on analised data. The used data belong to the molecular diagnostic area and are provided by Genex CZ company. The result is an analysis of probit analysis output data from Minitab 14 software. The thesis was supported by project from MSMT of the Czech Republic no. 1M06047 Center for Quality and Reliability of Production.

Clustering is the process of finding underlying group structure in data. As the scale of data collection continues to grow, this “big data” phenomenon results in more complex data structures. These data structures are not always compatible with traditional clustering methods, making their use problematic. This thesis presents methodology for analyzing samples of four-way and higher data, examples of these more complex data types. These data structures consist of samples of continuous data arranged in multidimensional arrays. A large emphasis is placed on clustering this data using mixture models that leverage tensor-variate distributions to model the data. Parameter estimation for all these methods are based on the expectation-maximization algorithm. Both simulated and real data are used for illustration. / Thesis / Doctor of Science (PhD)

<p> This thesis deals with metrizations of sets of conditional entropies and sets of sub-σ-algebras. G Co Rajski's Theorem ([9]) on the metric space of discrete probability distributions can be deduced as a particular case of a theorem on the metric space of sub-σ-algebras given in Chapter III, the proof of which is comparatively very concise. The completeness of this metric space and some other properties are also proved. </p> / Thesis / Master of Science (MSc)

Submitted by (ana.araujo@ufrpe.br) on 2016-05-25T17:33:53Z No. of bitstreams: 1 Cicero Carlos Ramos de Brito.pdf: 2928725 bytes, checksum: 35b3038da8b53c426368cd7ed2c96e03 (MD5) / Made available in DSpace on 2016-05-25T17:33:53Z (GMT). No. of bitstreams: 1 Cicero Carlos Ramos de Brito.pdf: 2928725 bytes, checksum: 35b3038da8b53c426368cd7ed2c96e03 (MD5) Previous issue date: 2014-08-07 / This work is divided into five chapters. The first one contains the objectives and the relevance of this study. In the second one, we review the literature presenting the state of the art in the field and we give an overview of the most used distributions which are the basis for the ones we generalize in later chapters. In the third chapter, the method for generating distributions is presented by means of a theorem and 7 corollaries. This method extends the probability distribution building process, so that the classes of distributions are constructed from pre-defined univariate monotonic functions and known distributions. In the fourth chapter, similarly to the third one, however, the construction was made from pre-defined multivariate monotonic functions and known multivariate distributions. We also conducted the development of new probability distributions and new generating functions of probability distribution classes. We illustrate the potentiality of this new univariate probability distribution we propose here by means of an application to an actual data set of excesses of flood peaks presented by Choulakian e Stephens (2001). For the application of the new multivariate distribution proposed, we used the database of measurements of Iris Flower exposed in Fisher’s work (1936). Six models were compared and, for their choice, we based on the Akaike Information Criterion (AIC), the Akaike Information Criterion corrected (AICc), Bayesian Information Criterion (BIC), the Hannan Quinn Information Criterion (HQIC) and the statistics of Cramér-von Mises and Anderson-Darling to assess the model fitting. Finally, we present the conclusions from de analyses, the comparisons from the results found in this thesis, the possibilities for research and ways to future works. / Este trabalho divide-se em cinco capítulos. No primeiro trazemos a introdução que contém os objetivos e a relevância deste estudo. No segundo, temos a revisão da literatura em que apresentamos o estado da arte deste campo do conhecimento e fazemos um apanhado das distribuições mais utilizadas que são base para as que generalizamos em capítulos posteriores. No terceiro capítulo, apresenta-se o método gerador, que é um teorema proposto com 7 corolários, que estende o processo de construções de distribuições de probabilidades, a fim de que as classes de distribuições sejam construídas a partir de funções monotônicas univariadas pré-definidas e distribuições conhecidas. No quarto capítulo foi trabalhado semelhantemente ao terceiro, entretanto, a construção se deu a partir das funções monotônicas multivariadas pré-definidas e distribuições multivariadas conhecidas. Também foi realizado o desenvolvimento das novas distribuições probabilísticas e novas funções geradoras de classes de distribuições probabilísticas. Ilustramos a potencialidade da nova distribuição de probabilidade univariada aqui proposta através de uma aplicação ao conjunto de dados reais de excessos de picos de enchentes apresentado em Choulakian e Stephens (2001). Para uma aplicação da nova distribuição multivariada proposta, utilizou-se a base de dados de medidas da Flor de Iris apresentada no trabalho de Fisher (1936). São comparados seis modelos e para a seleção desses modelos, foram utilizados o Critério de Informação de Akaike (AIC), o Critério de Informação de Akaike corrigido (AICc), o Critério de Informação Bayesiano (BIC), o Critério de Informação Hannan Quinn (HQIC) e as estatísticas de Cramer Von-Mises e de Anderson-Darling para avaliar o ajuste dos modelos. Por fim, apresentamos as conclusões a partir das análises e comparações dos resultados obtidos e direções a trabalhos futuros.

Master of Science / Department of Statistics / Suzanne Dubnicka / To help with identifying distributions to effectively model univariate continuous data, the R function diagnostic is proposed. The function will aid in determining reasonable candidate distributions that the data may have come from. It uses a combination of the Pearson goodness of fit statistic, Anderson-Darling statistic, Lin’s concordance correlation between the theoretical quantiles and observed quantiles, and the maximum difference between the theoretical quantiles and the observed quantiles. The function generates reasonable candidate distributions, QQ plots, and histograms with superimposed density curves. When a simulation study was done, the function worked adequately; however, it was also found that many of the distributions look very similar if the parameters are chosen carefully. The function was then used to attempt to decipher which distribution could be used to model weekly grocery expenditures of a family household.

Interindustry transactions recorded at a macro level are simply summations of commodity shipment decisions taken at a micro level. The resulting statistical problem is to obtain minimally biased estimates of commodity flow distributions at the disaggregated level, given various forms of aggregated information. This study demonstrates the application of the entropy-maximizing paradigm in its traditional form, together with recent adaptations emerging from information theory, to the area of spatial and non-spatial input-output analysis. A clear distinction between the behavioural and statistical aspects of entropy modelling is suggested. The discussion of non-spatial input-output analysis emphasizes the rectangular and dynamic extensions of Leontief's original model, and also outlines a scheme for simple aggregation, based on a criterion of minimum loss of information. In the chapters on spatial analysis, three complementary approaches to the estimation of interregional flows are proposed. Since the static formulations cannot provide an accurate picture of the gross interregional flows between any two sectors, Leontief's dynamic framework is adapted to the problem. The study concludes by describing a hierarchical system of models to analyse feasible paths of economic development over space and time. / digitalisering@umu

Unconventional resources will play an important role in filling the gap between supply and demand for future world energy. In North America, the impact of unconventional resources on energy supplies is growing continuously. However, around the world they have yet to serve as a major contributor to the energy supply, partly due to the scarcity of information about the exploration and development technologies required to produce them. Basin analogy can be used to estimate the undiscovered petroleum potential in a target basin by finding a geological analog that has been explored enough that its resource potential is fully understood. In 2006, Singh developed a basin analog system BASIN (Basin Analog Systems INvestigation) in detail that could rapidly and consistently identify analogous reference basins for a target basin. My research focused on continuing that work, comprehensively improving the basin analog system in four areas: the basin analog method; the database; the software functionality; and the validation methods. The updated system compares basins in terms of probability distributions of geological parameters. It compensates for data that are sparse or that do not represent basin-level geological parameters, and it expands the system's ability to compare widely varying quantitative parameters. Because the updated BASIN database contains more geologic and petroleum systems information on reference (existing) basins, it identifies analog basins more accurately and efficiently. The updated BASIN software was developed by using component-based design and data visualization techniques that help users better manage large volumes of information to understand various data objects and their complicated relationships among various data objects. Validation of the improved BASIN software confirms its accuracy: if a basin selected as the target basin appears in the reference basin list with other basins, the target basin is 100% analogous only to itself. Furthermore, when a target basin is analyzed by both BASIN and PRISE (Petroleum Resources Investigation and Summary Evaluation) software, results of the improved BASIN closely matched the PRISE results, which provides important support for using BASIN and PRISE together to quantitatively estimate the resource potential in frontier basins.

Šiame magistro baigiamajame darbe yra aiškiai ir plačiai nagrinėjami tikimybių teorijos dėsniai, aiškinamos pagrindinės savybės ir tarpusavio ryšiai. Yra taip pat pateikiama atsitiktinių dydžių serijos aproksimavimas vienu iš tų dėsnių. Dalinant ir dauginant nepriklausomus atsitiktinius dydžius vienus iš kitų randami nauji pasiskirstymai ir jų formos. Visa tai suprasti palengvina prieduose pateiktos vaizdinės išraiškos. / In this master thesis is clearly and widely considered laws of probability theory, explained the main features and mutual relations. There is also a series of random variables approximated by the one of those laws. There is given interest results of the product XY and the ratio X/Y where X and Y is randomly distributed variables. All that facilitates to understand added Additives with the visual expression.