In classic GARCH models for financial returns the innovations are usually assumed to be normally distributed. However, it is generally accepted that a non-normal innovation distribution is needed in order to account for the heavier tails often encountered in financial returns. Since the structure of the normal inverse Gaussian (NIG) distribution makes it an attractive alternative innovation distribution for this purpose, we extend the normal GARCH model by assuming that the innovations are NIG-distributed. We use the normal variance mixture interpretation of the NIG distribution to show that a NIG innovation may be interpreted as a normal innovation coupled with a multiplicative random impact factor adjustment of the ordinary GARCH volatility. We relate this new volatility estimate to realised volatility and suggest that the random impact factors are due to a news noise process influencing the underlying returns process. This GARCH model with NIG-distributed innovations leads to more accurate parameter estimates than the normal GARCH model. In order to obtain even more accurate parameter estimates, and since we expect an information gain if we use more data, we further extend the model to cater for high, low and close data, as well as full intraday data, instead of only daily returns. This is achieved by introducing the Brownian inverse Gaussian (BIG) process, which follows naturally from the unit inverse Gaussian distribution and standard Brownian motion. Fitting these models to empirical data, we find that the accuracy of the model fit increases as we move from the models assuming normally distributed innovations and allowing for only daily data to those assuming underlying BIG processes and allowing for full intraday data. However, we do encounter one problematic result, namely that there is empirical evidence of time dependence in the random impact factors. This means that the news noise processes, which we assumed to be independent over time, are indeed time dependent, as can actually be expected. In order to cater for this time dependence, we extend the model still further by allowing for autocorrelation in the random impact factors. The increased complexity that this extension introduces means that we can no longer rely on standard Maximum Likelihood methods, but have to turn to Simulated Maximum Likelihood methods, in conjunction with Efficient Importance Sampling and the Control Variate variance reduction technique, in order to obtain an approximation to the likelihood function and the parameter estimates. We find that this time dependent model assuming an underlying BIG process and catering for full intraday data fits generated data and empirical data very well, as long as enough intraday data is available. / Thesis (Ph.D. (Risk Analysis))--North-West University, Potchefstroom Campus, 2006.

Recent shifts towards ecosystem based fisheries management (EBFM) around the world have necessitated consideration of effects of fishing on a larger range of species than previously. Non-selective multispecies fisheries are particularly problematic for EBFM, as they can contribute to erosion of ecosystem structure. The trade-off between catch of productive commercial species and abundance of low-productivity species is unavoidable in most multispecies fisheries. A first step in evaluation of this trade-off is estimation of productivity of different species but this is often hampered by poor data. This thesis develops techniques for estimating productivity for data-limited species and aims to help clarify EBFM policy objectives for the fisheries of New South Wales (NSW), Australia. It begins with development of an age-structured model parameterised in terms of optimal harvest rate, UMSY. UMSY is a measure of productivity, comparable among species and easily communicated to managers. It also represents a valid threshold for prevention of overfishing. The model is used to derive UMSY for 54 Atlantic fish stocks for which recruitment parameters had previously been estimated. In most cases, UMSY was strongly limited by the age at which fish were first caught. However, for some species, UMSY was more strongly constrained by life history attributes. The model was then applied to twelve species of Australian deepwater dogshark (Order Squaliformes), known to have been severely depleted by fishing. Results showed that the range of possible values of UMSY for these species is very low indeed. These findings enabled a preliminary stock assessment for three dogsharks (Centrophorus spp.) currently being considered for threatened species listing. Preliminary results suggest they have been overfished and that overfishing continues. Finally, an Ecopath with Ecosim ecosystem model, representing the 1976 NSW continental slope, is used to illustrate trade-offs in implementation of fishing policies under alternative policy objectives. Results are compared with those of a biogeochemical ecosystem model (Atlantis) of the same system, built by scientists from CSIRO. While there were large differences in model predictions for individual species, they gave similar results when ranking alternative fishing policies, suggesting that ecosystem models may be useful for exploring broad-scale strategic management options.

This study is one of the first studies to fully address the relationship that business-to-business buyers have with both the selling firm and salesperson within an integrated model. Finding from this survey research support 14 of the 26 original hypotheses and the 2 additional linkages using structural equation modeling. This study finds that the relationship customers have with the selling firm is a stronger predictor of continuance than the relationship that the buyer has with the salesperson. While this relationship is stronger between the buyer and the selling firm, findings suggest that the salesperson can have a direct negative impact on the relationship if conflict is present. Overall, this study provides a framework for future research on the topic of business-to-business buyer-selling firm and buyer-salesperson relationships.

Darbe pasiūlyta tempiamojo betono įtempių - deformacijų priklausomybė trumpalaikio ir ilgalaikio apkrovimo atveju. Pasiūlyta priklausomybė gauta, taikant EC2 momentų–kreivių priklausomybių apskaičiavimo metodiką. Atlikta lenkiamųjų gelžbetoninių elementų įtempių ir deformacijų priklausomybių analizė. Apžvelgti tokių elementų deformacijų skaičiavimo metodai ir matematiniai modeliai, apžvelgti paskelbti literatūros šaltiniai, susijusę su lenkiamųjų gelžbetoninių elementų deformacijomis. Skaitinio eksperimento pagalba sudaryta lenkiamųjų gelžbetoninių elementų duomenų imtis, išnagrinėta trumpalaike ir ilgalaike apkrova veikiami lenkiamieji gelžbetoniniai elementai, deformacijos ir jas lemiantys faktoriai, atlikta jų analizė. Taikant VGTU tiltų ir specialiųjų statinių katedroje pasiūlytą sluoksnių metodą iš skaitinių eksperimentų gautų momentų-kreivių diagramų gautos supleišėjusio tempiamojo betono įtempių-deformacijų priklausomybės. Parinkti pagrindiniai teorinės diagramos parametrai, priklausomai nuo betono klasės, armavimo procento bei valkšnumo koeficiento. Gautoji priklausomybė pritaikyta gelžbetoninių sijų kreivių apskaičiavimui sluoksnių metodu. Gautieji rezultatai palyginti su empirinėmis EC2 normų prikalsumybėmis gautais rezultatais. Palyginamoji gautų skaičiavimo rezultatų analizė parodė gerą abiem metodais gautų rezultatų atitikimą. Gautoji priklausomybė gali būti pritaikyta netiesiniuose skaičiavimuose, taikant baigtinių elementų metodą. / The paper suggests tension concrete stress-strain dependence of the short-term and long-term case-load of the EC2 method. Bending reinforced concrete elements of stress and strain dependence are analyzed. Presented overview of such elements deformation calculation methods and mathematical models, highlight the relevance literature review, relating to bending reinforced concrete elements. Collected bending reinforced concrete elements (numerical experiments) data, examined short-term and long term effects of load to bended reinforced concrete elements, deformations and the determining factors, performed their analysis. For the purposed of VGTU bridges and special structures department’s constitutive model from the numerical experiments obtained moment-curvature relationships derived the charts of cracked pulling concrete stress-strain dependence. Choose the basic theoretical parameters of the relationships, depending on the class of concrete, reinforcement rates, and creep coefficient. The calculation results are compared with the experimental beam data. Performed calculation results of the analysis showed quite accurate results with the derived dependencies.

Analizuojama viena aktualiausių šių dienų problemų Lietuvoje – narkomanija, kuri sąlygoja nusikalstamumą, pavojingų ligų plitimą. Remiantis moksline literatūra ir Bažnyčios dokumentais apie narkomanijos plitimą, aiškinami veiksniai, formuojantys polinkį į narkomaniją, apžvelgiamas statistinis Lietuvos narkomanijos vaizdas, aiškinamos prevencinės galimybės, Bažnyčios įtaka. Atliktas kokybinis tyrimas. / In this work is analysed one of topical issues in Lithuania – the drug habit, what determine the delinquency, dangerous illness and the like. On the ground of research literature and writing of Church about the spread of drug are explained the factors, what formed it. It is under review the statistical view of drug in Lithuania, are analysed the preventive chances, the influence of Church.

Many insurance and finance activities involve multiple risks. Dependence structures between different risks play an important role in both theoretical models and practical applications. However, stochastic and actuarial models with dependence are very challenging research topics. In most literature, only special dependence structures have been considered. However, most existing special dependence structures can be integrated into more-general contexts. This thesis is motivated by the desire to develop more-general dependence structures and to consider their applications. This thesis systematically studies different dependence notions and explores their applications in the fields of insurance and finance. It contributes to the current literature in the following three main respects. First, it introduces some dependence notions to actuarial science and initiates a new approach to studying optimal reinsurance problems. Second, it proposes new notions of dependence and provides a general context for the studies of optimal allocation problems in insurance and finance. Third, it builds the connections between copulas and the proposed dependence notions, thus enabling the constructions of the proposed dependence structures and enhancing their applicability in practice. The results derived in the thesis not only unify and generalize the existing studies of optimization problems in insurance and finance, but also admit promising applications in other fields, such as operations research and risk management.

Depending on the role of software in everyday life, the cost of a software failure can sometimes be unaffordable. During system execution, errors may occur in system components and failures may be manifested due to these errors. These errors differ with respect to their effects on system behavior and consequent failure manifestation manners. Predicting failures before their manifestation is important to assure system resilience. It helps avoid the cost of failures and enables systems to perform corrective actions prior to failure occurrences. However, effective runtime error detection and failure prediction techniques encounter a prohibitive challenge with respect to the control flow representation of large software systems with intricate control flow structures. In this thesis, we provide a technique for failure prediction from runtime errors of large software systems. Aiming to avoid the possible difficulties and inaccuracies of the existing Control Flow Graph (CFG) structures, we first propose a Connection Dependence Graph (CDG) for control flow representation of large software systems. We describe the CDG structure and explain how to derive it from program source code. Second, we utilize the proposed CDG to provide a connection-based signature approach for control flow error detection. We describe the monitor structure and present the error checking algorithm. Finally, we utilize the detected errors and erroneous state parameters to predict failure occurrences and modes during system runtime. We craft runtime signatures based on these errors and state parameters. Using system error and failure history, we determine a predictive function (an estimator) for each failure mode based on these signatures. Our experimental evaluation for these techniques uses a large open-source software (PostgreSQL 8.4.4 database system). The results show highly efficient control flow representation, error detection, and failure prediction techniques. This work contributes to software reliability by providing a simple and accurate control flow representation and utilizing it to detect runtime errors and predict failure occurrences and modes with high accuracy. / Thesis (Ph.D, Computing) -- Queen's University, 2012-09-25 23:44:12.356

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<p><font face="Times New Roman"> <p align="left">The aims of this study were therefore to describe the personal experiences of a methamphetamine addict as well as the effects of this addiction on the family&rsquo / s communication and problem-solving abilities.</p> </font></p>

The associations between maternal smoking and nicotine dependence and patterns of smoking and nicotine dependence in offspring were examined in a large community-based sample of adolescents. Data were derived from baseline and 4-year follow-up assessments of 938 respondents aged 14–17 years at the outset of the Early Developmental Stages of Psychopathology (EDSP) study, a prospective-longitudinal community study of adolescents and young adults and their parents respectively. Smoking and nicotine dependence in respondents were assessed using the Munich Composite International Diagnostic Interview (DSM-IV algorithms). Diagnostic information about smoking behavior in mothers was collected by independent direct diagnostic interviews with the mothers. In comparison to children of non- or occasionally smoking mothers, children of regularly smoking and nicotine-dependent mothers had higher probabilities of using tobacco as well as of developing nicotine dependence. For all ages under consideration, survival analyses revealed a higher cumulative lifetime risk of regular smoking and nicotine dependence among these children. Maternal smoking during pregnancy seems to represent an additional risk for these outcomes in children, specifically with regard to the risk of developing nicotine dependence. Associations were comparable for sons and daughters. Our findings show that maternal smoking predicts escalation of smoking, development of nicotine dependence, and stability of smoking behavior in children. Implications for specific intervention and prevention efforts are discussed.