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Extreme value distribution quantile estimationBuck, Debra L. January 1983 (has links)
This thesis considers estimation of the quantiles of the smallest extreme value distribution, sometimes referred to as the log - Weibull distribution. The estimators considered are linear combinations of two order statistics. A table of the best linear estimates (BLUE's) is presented for sample sizes two through twenty. These estimators are compared to the asymptotic estimators of Kubat and Epstein (1980).
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Effects of high-altitude trekking on body compositionFrisk, Ulrika January 2014 (has links)
Sojourns at high altitude are often accompanied by weight loss and changes in body composition. The aim was to study body composition before and after 40 days high-altitude exposure. The subjects were four women and six men, non-smoking, healthy and active students and a scientist from Mid Sweden University in Östersund with a mean (SD) age of 26 (10) years. All subjects volunteered for a six-week trek to the Mount Everest Base Camp via Rolwaling in Nepal. Before the sojourn subject’s height was 177 (10) cm and weight was 71.9 (10) kg. Body composition was measured with Lunar iDXA at the Swedish Winter Sports Research Centre in Östersund before and after the trek. Total body mass (SD) decreased from 71.8 (10.0) kg before to 69.7 (9.4) kg after the trek (P=0.00). Total fat mass decreased from 14.7 (5.9) kg to 13.8 (4.6) kg (P=0.01). Fat percent decreased from 21.6 (7.9) % to 21.0 (7.2) % (P=0.03). Total lean mass decreased from 54.0 (10.0) kg to 52.9 (9.7) kg (P=0.01). Bone mineral content was unchanged, 3.04 (0.5) kg before and 3.03 (0.5) after (P=0.13). Thus both total body mass and total lean mass had decreased after a six week trekking in Nepal.
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The ionization and dissociation of selected molecules by VUV photonsSands, Anita Mary January 2001 (has links)
No description available.
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Physiological monitoring during the bicycle Race Across America (RAAM) : a case studySaldanha, Paulo. January 2000 (has links)
The purpose was to describe the physiological response and nutritional consumption of one athlete competing in the RAAM. The 1999 RAAM covered 4727 kilometers from Irvine, CA. to Savannah, GA. The subject was a 36 year-old male elite triathlete with 12 years of training experience. VO2max was 4.32 L/min. Prior to RAAM, cycling economy was measured at 100 and 150 watts. During RAAM, the following measurements were continuously recorded: heart rate, power output, nutritional intake, and body mass. Power output was recorded using a hub dynamometer (4 strain gauges, PowerTap). The subject completed RAAM in 10.1 days and spent 18.6 h/day cycling. Mean cycling values for power output, mechanical energy and heart rate were: 97 watts, 6676 kjoules and 99 b/min. Daily cycling energy expenditure was 7,946 +/- 1435 kcal/day. Energy intake averaged 6,812 +/- 914 kcal/day with 67% CHO, 24% fat, and 9% protein. Body mass decreased by 2.5 kg and percent fat decreased from 9.2% to 7.1%.
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Extreme Value Theory with an Application to Bank Failures through ContagionNikzad, Rashid 03 October 2011 (has links)
This study attempts to quantify the shocks to a banking network and analyze the transfer of shocks through the network. We consider two sources of shocks: external shocks due to market and macroeconomic factors which impact the entire banking system, and idiosyncratic shocks due to failure of a single bank. The external shocks will be estimated by using two methods: (i) non-parametric simulation of the time series of shocks that occurred to the banking system in the past, and (ii) using the extreme value theory (EVT) to model the tail part of the shocks. The external shocks we considered in this study are due to exchange rate and treasury bill rate volatility. Also, an ARMA/GARCH model is used to extract iid residuals for this purpose. In the next step, the probability of the failure of banks in the system is studied by using Monte Carlo simulation. We calibrate the model such that the network resembles the Canadian banking system.
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Stochastic Simulation Methods for Precipitation and Streamflow Time SeriesLi, Chao 03 October 2013 (has links)
One major acknowledged challenge in daily precipitation is the inability to model extreme events in the spectrum of events. These extreme events are rare but may cause large losses. How to realistically simulate extreme behavior of daily precipitation is necessary and important. To that end, a hybrid probability distribution is developed. The logic of this distribution is to simulate the low to moderate values by an exponential distribution and extremes by a generalized Pareto distribution. Compared with alternatives, the developed hybrid distribution is capable of simulating the entire range of precipitation amount and is much easier to use. The hybrid distribution is then used to construct a bivariate discrete-continuous mixed distribution, which is used for building a daily precipitation generator. The developed generator can successfully reproduce extreme events. Compared with other widely used generators, the most important advantage of the developed generator is that it is apt at extrapolating values significantly beyond the upper range of observed data.
The major challenge in monthly streamflow simulation is referred to the underrepresentation of inter-annual variability. The inter-annual variability is often related with sustained droughts or periods of high flows. Preserving inter-annual variability is thus of particular importance for the long-term management of water resources systems. To that end, variables conveying such inter-annual signals should be used as covariates. This requires models that must be flexible at incorporating as many covariates as necessary. Keeping this point in mind, a joint conditional density estimation network is developed. Therein, the joint distribution of streamflows of two adjacent months is assumed to follow a specific parametric family. Parameters of the distribution are estimated by an artificial neural network. Due to the seasonal concentration of precipitation or the joint effect of rainfall and snowmelt, monthly streamflow distribution sometimes may exhibit a bimodal shape. To reproduce bimodality, nonparametric models are often preferred. However, the simulated sequences from existing nonparametric models represent too close a resemblance to historical record. To address this issue, while retaining typical merits of nonparametric models, a multi-model regression-sampling algorithm with a few weak assumptions is developed.
Collecting hydrometric data is the first step for building hydrologic models, and for planning, design, operation, and management of water resource systems. In this dissertation, an entropy-theory-based criterion, termed maximum information minimum redundancy, is proposed for hydrometric monitoring network evaluation and design. Compared with existing similar approaches, the criterion is apt at finding stations with high information content, and locating independent stations.
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Far tail or extreme day returns, mutual fund cash flows and investment behaviourBurnie, David A., de Ridder, Adri January 2010 (has links)
This study examines the frequency of extreme trading days and investment behaviour in Sweden. We show that the frequency, as well as the magnitude of extreme trading days has increased over time. We also show that the frequency of extreme trading days in a year is positively correlated to the frequency the preceding year. Furthermore, we show that aggregate cash flows into equity and bond funds are unrelated to risk measured by standard deviation of return. Our findings show that investors, individuals as well as corporations, use simple passive investment strategies and hence, do not believe in market timing or wish to risk capital on capturing far tail or black swan type returns.
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Extreme-day return as a measure of stock market volatility : comparative study developed vs. emerging capital markets of the worldKabir, Muashab, Ahmed, Naeem January 2010 (has links)
This paper uses a new measure of volatility based on extreme day return occurrences and examines the relative prevailing volatility among worldwide stock markets during 1997-2009. Using several global stock market indexes of countries categorized as an emerging and developed capital markets are utilized. Additionally this study investigates well known anomalies namely Monday effect and January effect. Further using correlation analysis of co movement and extent of integration highlights the opportunities for international diversification among those markets. Evidences during this time period suggest volatility is not the only phenomena of emerging capital markets. Emerging markets offer opportunities of higher returns during volatility. Cross correlation analysis depicts markets have become more integrated during this time frame; still opportunities for higher returns prevail through global portfolio diversification.
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Extreme dude! a phenomenological perspective on the extreme sport experience /Brymer, George Eric. January 2005 (has links)
Thesis (Ph.D.)--University of Wollongong, 2005. / Typescript. Includes bibliographical references: p. 319-354.
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A model for the application of arbitrary object-oriented refactorings /Gayed, Grant January 1900 (has links)
Thesis (M.C.S.) - Carleton University, 2002. / Includes bibliographical references (p. 116-119). Also available in electronic format on the Internet.
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