This thesis describes fundamental analysis method based on a price to earnings ratio and an effort is put on the following areas: (i) empirical verification of factors determining the price to earnings ratio, (ii) empirical verification of an investment strategy based on historical price to earnings ratios and (iii) behavior of P/Es in bear market periods. The empirical verification of the main factors determining the price to earnings ratio is conducted on empirical data for a sample of eleven stocks listed on Prague Stock Exchange in period 2006-2011. The empirical verification of macroeconomic factors determining the price to earnings ratio as well as the empirical verification of an investment strategy based on historical price to earnings ratios are researched based on empirical data of an equity index S&P 500 in period 1954-2011 and an equity index PX in period 2001-2011. Behavior of P/Es in bear markets is researched on empirical data of index S&P 500 in period 1954-2011 and index PX in period 2001-2011.

Soil moisture is a key variable in off-road mobility. Mobility analysis was conducted based on three soil moisture sources: WindSat (a satellite), LIS (a computer model), and in situ ground sensors (assumed to represent ground truth). Mobility of six vehicles, each with different ranges of sensitivity to soil moisture, was examined in three test sites. Two methods were used: a simplified method based on time series and a fulleatured terrain method. The results demonstrated that the effect of the soil moisture error on mobility predictions is complex and may produce very significant errors in mobility analysis for certain combinations of vehicles, seasons, and climates. Soil moisture biases vary in both direction and magnitude with season and location. Furthermore, vehicles are sensitive to different ranges of soil moistures. In the wet season, differences in soil strength resulted in more significant differences in mobility predictions than in the dry season.

The classical Extreme Value Theory deals with independent random variables. If random variables are dependent, large values tend to cluster (that is, one large value is followed by a series of large values). It is of interest to describe probabilistically the clustering and estimate the relevant cluster functionals. We consider disjoint blocks, sliding blocks and runs estimators of cluster indices. Using a modern theory of multivariate, regularly varying time series, we obtain consistency results and central limit theorems under conditions that can be easily verified for a large class of short-range dependent models. In particular, we show that in the Peak-over-Threshold framework, all the estimators have the same limiting variances. This solves a longstanding open problem and is in contrast to the Block Maxima method. Our findings are illustrated by simulation experiments.

As more dams experience spillway flows from flood events, identification and analysis of erosion in auxiliary rock surface spillways has become a primary focus in maintaining dam integrity. The spillway erosion risk assessment developed for this research is based on parameters identified and discussed in previous research as the leading factors influencing spillway damage from erosion. Parameters applied in this analysis were channel geometry, stream hydrology, and geologic materials. Channel geometry is described by the length of spillway channel and slope of the spillway floor; stream hydrology is classified by the peak discharge and its duration; and geologic material is identified by its behavior in resisting erosion. The Sites Spillway Erosion Analysis (SSEA) was used to produce a risk assessment based on U.S. Army Corps of Engineers case histories. The risk assessment was used to classify and refine model uncertainties, an important advancement in evaluating spillway erosion.

Location plays an ever increasing role in modern web-based applications. Many of these applications leverage off-the-shelf search engine technology to provide interactive access to large collections of data. Unfortunately, these commodity search engines do not provide special support for location-based indexing and retrieval. Many applications overcome this constraint by applying geographic bounding boxes in conjunction with range queries. We propose an alternative technique based on geographic identifiers and suggest it will yield faster query evaluation and provide higher search precision. Our experiment compared the two approaches by executing thousands of unique queries on a dataset with 1.8 million records. Based on the quantitative results obtained, our technique yielded drastic performance improvements in both query execution time and precision.

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Yes / In this paper, we focus on the financial and fiscal stress transmission for the G5 economies. Using financial and fiscal stress indexes, we assess the spillovers within each economy, as well as the cross-sectional effects. Two supplementary methodologies, measuring the degree of interconnectedness, are employed. Our findings indicate that the interactions between these two kinds of distress are intensive, especially during and after the Global Financial Crisis outbreak. The above reiterates the necessity for coordinated macroprudential policies, as a means to confine the adverse effects of excessive financial and fiscal stress.

Master of Science / Department of Statistics / Perla Reyes Cuellar / A frost index is a calculated value that can be used to describe the state and the changes in the weather conditions. Frost indices affect not only natural and managed ecosystems, but also a variety of human activities. In addition, they could indicate changes in extreme weather and climate events. Growing season length is one of the most important frost indices. In this report, growing season lengths were collected from 23 long-term stations over Kansas territory. The records extended to the late 1800s for a few stations, but many started observations in the early 1900s. Though the start dates of the records were different, the end dates were the same (2009). To begin with, time series models of growing season length for all the stations were fitted. In addition, by using fitted time series models, predictions and validation checking were conducted. Then a regular linear regression model was fitted for the GSL data. It removed the temporal trend by doing regression on year and it showed us the relationship between GSL and elevation. Finally, based on a penalized likelihood method with least angle regression (LARS) algorithm, spatial-temporal model selection and parameter estimation were performed simultaneously. Different neighborhood structures were used for model fitting. The spatial-temporal linear regression model obtained was used for interpreting growing season length of those stations across Kansas. These models could be used for agricultural management decision-making and updating recommendations for planting date in Kansas area.

Master of Science / Department of Agricultural Economics / Ted Schroeder / Demand indices are used by many industries as a measurement tool to track changes and make yearly comparisons. Many different sources use demand indices to track the demand for beef. Indexes are an important tool to help better understand why demand shifts the way that it does and help strategically plan for the future of the industry. There are a wide variety of beef demand indices out in academia and many are constructed in different ways. This study advances the literature by testing which factors of index construction effect the results the greatest. This study tested four separate factors in the construction of demand indices. These iterations are as follows, changes in retail price data, changes in elasticities chosen, changes in export data, and changes in construction in terms of quantities instead of prices. Changes in retail price data do not appear to be statistically different. All estimates in this study where elasticities were changed appear to be different statistically, however the level of concern with this finding may be minimal due to the small increments of change in magnitudes of difference between indices. Results from omitting export data does appear to result in statistically different indices, but again the level of concern with the difference may be small. Finally, index construction in terms of prices versus construction in terms of quantities does not appear to have statistically different results, as the indices in this comparison move similarly. For all practical purposes in industry, it does not appear to matter which index is chosen for comparisons, as long as one remains consistent with which index is chosen for comparisons.

Šio darbo tikslas – pasiulyti nauja algoritma muzikos kuriniu indeksacijai ir paieškai. Tikslui pasiekti formuluojami uždaviniai ir reikalavimai naujai pasiulytam algoritmui. Taip pat darbe išnagrinejami šiuo metu naudojami algoritmai muzikos indeksacijai ir paieškai. Kitoje darbo dalyje pateikiamas algoritmas, kuriam naudojami Teiloro koeficientai padeda išskirti muzikos požymius. Išskirtu muzikos požymiu palyginimui pateikiamos dvi algoritmo versijos: greitoji versija, kuri naudojasi hash raktais, ir letoji versija, naudojanti daugiau duomenu muzikos palyginimui. Rasti algoritmai testuojami eksperimentineje darbo dalyje – tikrinamas algoritmu atsparumas triukšmui, ju priklausomybe nuo užklausos trukmes. Taip pat algoritmu rezultatai lyginami ir su kitais algoritmais. Gauti rezultatai parodo, kad algoritmai geba atpažinti muzikos kurini esant trisdešimt penkiu decibelu triukšmui tik iš trisdešimties sekundžiu irašo. / The goal of this work is to propose a new algorithm for music indexing and searching. To achieve this, objectives and requirements were formulated for the newly proposed algorithm. State of the art algorithms for music indexing and searching were also examined. Following that, an algorithm that uses Taylor coefficients to distinguish music features was suggested. To compare music features, two algorithm versions were suggested: a quick version th at uses hash keys, and a slow version, using more data to compare the music. The suggested algorithms are tested in the experimental part. Noise immunity and their dependence on the length of the query are checked. The results are compared with those of th e state of the art algorithms. They show that the algorithm is able to recognize a music that has thirty - five decibel noise and only from a thirty seconds query.