No description available.

In this dissertation we present a novel computational method, as well as its software implementation, to compare two samples by a nonparametric likelihood-ratio test. The basis of the comparison is a mean-type hypothesis. The software is written in the R-language [4]. The two samples are assumed to be independent. Their distributions, which are assumed to be unknown, may be discrete or continuous. The samples may be uncensored, right-censored, left-censored, or doubly-censored. Two software programs are offered. The first program covers the case of a single mean-type hypothesis. The second program covers the case of multiple mean-type hypotheses. For the first program, an approximate p-value for the single hypothesis is calculated, based on the premise that -2log-likelihood-ratio is asymptotically distributed as ­­χ2(1). For the second program, an approximate p-value for the p hypotheses is calculated, based on the premise that -2log-likelihood-ratio is asymptotically distributed as ­χ2(p). In addition we present a proof relating to use of a hazard-type hypothesis as the basis of comparison. We show that -2log-likelihood-ratio is asymptotically distributed as ­­χ2(1) for this hypothesis. The R programs we have developed can be downloaded free-of-charge on the internet at the Comprehensive R Archive Network (CRAN) at http://cran.r-project.org, package name emplik2. The R-language itself is also available free-of-charge at the same site.

This thesis consists of two parts: the first examines the Expectations Hypothesis of the Term Structure for New Zealand, and the latter examines the predictive power of the term spread on future economic activity in New Zealand. For both parts, I divide the sample period into two sub-sample periods – the pre-OCR period and the OCR period. Using Mankiw & Miron’s (1986) approach for testing the expectations hypothesis, the findings in this paper suggest that the theory is consistent with New Zealand data during the OCR period. I attribute the success of the theory to the introduction of the Official Cash Rate system in March 1999. The change from targeting the settlement cash balance to targeting an interest rate variable has substantially improved the predictability of short-term interest rates. In regards to the predictive power of the spread, the findings in this paper support the conventional view that the spread is positively related to future economic activity. Using Hamilton & Kim’s (2002) approach, I decomposed the term spread into an expectation component and a term premium in an attempt to find out whether these two variables have distinctly separate effect on future economic activity. My findings are in contrast to that reported by Hamilton & Kim. In particular, I find that the term premium in some cases is significant and negatively related to future economic activity in New Zealand. I attribute the negative relationship to lower long-term interest rates and a fallen term premium in New Zealand.

During the lifetime of an organism, key events are orchestrated by a confluence of environmental, social, and physiological factors to promote reproductive success. Steroid hormones are critical regulators of fundamental aspects of reproductive life history, including gametogenesis, secondary sexual characteristics, sexual behavior, territory establishment and defense, and parenting. The steroid hormones investigated herein (testosterone (T), 11-ketotestosterone (KT), 17b-estradiol (E2) and cortisol) are linked through steroidogenic conversion pathways. This dissertation utilized an integrative approach to investigate the neuroendocrine and social contexts that regulate transitions among phenotypes in a bi-directionally hermaphroditic haremic fish, Lythrypnus dalli. Conventional sex roles are reversed, such that only males provide nest care, females exhibit intra-sexual competition and male reproductive success is associated with female courtship solicitation. Females living in stable social groups maintain dramatic differences in status, morphology, and tissue T, KT, E2, and cortisol. Parasitic male morphs, mini males, do not defend territories and have morph-typical water-borne and tissue profiles of T, E2, and KT. Two life history transitions, socially induced sex change and male parenting, are associated with increase in rates of behavior and KT levels. The regulation of these life history transitions by KT was investigated via two types of endocrine manipulations. Coupling systemic KT implants with a social context permissive to sex change caused rapid, but transient effects on agonistic behavior in dominant females, and secondary effects on subordinates during a period of social instability. Despite elevated brain and systemic KT 5 d after implant, overall rates of aggressive behavior remained unaffected, demonstrating a key role for context in regulating steroid associated changes in behavior. Intracerebroventricular inhibition of the enzyme 11b-hydroxysteroid dehydrogenase, reduced KT, elevated cortisol, and reduced male parenting behavior. 11-Ketotestosterone rapidly rescued parenting when administered along with the inhibitor, while cortisol had no effects on parenting. During reduced male nest attendance caused by KT inhibition, dominant, but not subordinate females, exhibited transient parenting and elevated brain KT. Taken together, rapid and/or local modulation of steroids allows for context-specific regulation of dynamic changes in behavior in an environment that requires an organism to successfully coordinate multiple activities to enhance fitness.

During the lifetime of an organism, key events are orchestrated by a confluence of environmental, social, and physiological factors to promote reproductive success. Steroid hormones are critical regulators of fundamental aspects of reproductive life history, including gametogenesis, secondary sexual characteristics, sexual behavior, territory establishment and defense, and parenting. The steroid hormones investigated herein (testosterone (T), 11-ketotestosterone (KT), 17b-estradiol (E2) and cortisol) are linked through steroidogenic conversion pathways. This dissertation utilized an integrative approach to investigate the neuroendocrine and social contexts that regulate transitions among phenotypes in a bi-directionally hermaphroditic haremic fish, Lythrypnus dalli. Conventional sex roles are reversed, such that only males provide nest care, females exhibit intra-sexual competition and male reproductive success is associated with female courtship solicitation. Females living in stable social groups maintain dramatic differences in status, morphology, and tissue T, KT, E2, and cortisol. Parasitic male morphs, mini males, do not defend territories and have morph-typical water-borne and tissue profiles of T, E2, and KT. Two life history transitions, socially induced sex change and male parenting, are associated with increase in rates of behavior and KT levels. The regulation of these life history transitions by KT was investigated via two types of endocrine manipulations. Coupling systemic KT implants with a social context permissive to sex change caused rapid, but transient effects on agonistic behavior in dominant females, and secondary effects on subordinates during a period of social instability. Despite elevated brain and systemic KT 5 d after implant, overall rates of aggressive behavior remained unaffected, demonstrating a key role for context in regulating steroid associated changes in behavior. Intracerebroventricular inhibition of the enzyme 11b-hydroxysteroid dehydrogenase, reduced KT, elevated cortisol, and reduced male parenting behavior. 11-Ketotestosterone rapidly rescued parenting when administered along with the inhibitor, while cortisol had no effects on parenting. During reduced male nest attendance caused by KT inhibition, dominant, but not subordinate females, exhibited transient parenting and elevated brain KT. Taken together, rapid and/or local modulation of steroids allows for context-specific regulation of dynamic changes in behavior in an environment that requires an organism to successfully coordinate multiple activities to enhance fitness.

Concern is mounting over the increase in prevalence and severity of overweight and obesity in children worldwide. Intrauterine life has been identified as a critical period for the development of overweight or obesity and other related chronic diseases. Prenatal exposure to maternal cigarette smoke (PEMCS) has consistently emerged as an important risk factor for excess weight in the offspring and is a targetable behaviour for prevention strategies. This study examines first the relationship between PEMCS and overweight status of children at 10 years of age and second, whether PEMCS is associated with distinct longitudinal BMI trajectories. Analyses include multivariate and multinomial logistic regression and longitudinal group based modeling methods. PEMCS was found to be a significant risk factor for overweight in children independent of birth weight and catch-up growth. However, PEMCS was not associated with BMI trajectory membership. Our results lend support to the paradigm of in-utero excess weight prevention.

国立情報学研究所で電子化したコンテンツを使用している。

During the last few years nonlinear models have been a very active area of econometric research: new models have been introduced and existing ones generalized. To a large extent, these developments have concerned models in which the conditional moments are regime-dependent. In such models, the different regimes are usually linear and the change between them is governed by an observable or unobservable variable. These specifications can be useful in situations in which it is suspected that the behaviour of the dependent variable may vary between regimes. A classical example can be found the business cycle literature where it is argued that contractions in the economy are not only more violent but also short-lived than expansions. Unemployment, which tends to rise faster during recessions than decline during booms, constitutes another example. Two of the most popular regime-dependent models are the smooth transition and the threshold model. In both models cases the transition variable is observable but the specification of the way in which the model changes from one regime to the other is different. Particularly, in the smooth transition model the change is a continuous whereas in the threshold model it is abrupt. One of the factors that has influenced the development of nonlinear models are improvements in computer technology. They have not only permitted an introduction of more complex models but have also allowed the use of computer-intensive methods in hypothesis testing. This is particularly important in nonlinear models because there these methods have proved to be practical in testing statistical hypothesis such as linearity and parameter constancy. In general, these testing situation are not trivial and their solution often requires computer-intensive methods. In particular, bootstrapping and Monte Carlo testing are now commonly used. In this thesis the smooth transition model is used in different ways. In the first chapter, a vector smooth transition model is used as a device for deriving a test for parameter constancy in stationary vector autoregressive models. In the second chapter we introduce a panel model whose parameters can change in a smooth fashion between regimes as a function of an exogenous variable. The method is used to investigate whether financial constraints affect firms' \ investment decisions. The third chapter is concern with linearity testing in smooth transition models. New tests are introduced and Monte Carlo testing techniques are shown to be useful in achieving control over the size of the test. Finally, the last chapter is devoted to the Smooth Permanent Surge model. This is a nonlinear moving average model in which a shock can have transitory or permanent effects depending on its sign and magnitude. Test for linearity and random walk hypothesis are introduced. / Diss. Stockholm : Handelshögsk., 2004

Research Doctorate - Doctor of Philosophy (PhD) / The purpose of rainfall-runoff modelling, like all environmental modelling is to generate simulations that accurately mimic those encountered in the system being modelled. Once this is achieved, the model may then be used to study the catchment response under conditions that have not previously been observed, such as the determination of extreme flood levels. The complex behaviour of the processes involved in the generation of streamflow mean that to achieve a usable model, simplifications must be made. This inevitably leads to the introduction of model error into the simulations, as these simplifications cannot reproduce the level of response variation encountered in a natural system. As a consequence, a model that performs well at some times may be inappropriate at other times. The MultiModel approach is an alternative method of rainfall-runoff modelling that uses numerous alternative process descriptions to generate a suite of unique rainfall runoff models. These models are calibrated and applied to allow for simulation responses that incorporate not only parameter variability but model structure variability. It is shown that the application of the MultiModel method to four test catchments produced simulated confidence limits that are much more likely to contain flood peaks that are beyond the range encountered during the calibration process than using a single model. This is due to the wider confidence limits generated as a result of the greater structure variability available to the MultiModel. The wider confidence limits are therefore a better reflection of our true understanding of the system being modelled. The prediction of ungauged basins presents an additional challenge to rainfallrunoff modelling. Most methods involve some form of regionalization of model parameters. These approaches are very limited in that they are restricted by model selection and application range. Two unique methods for the prediction of ungauged basins are presented that overcome these restrictions. The first attempts to condition a rainfall-runoff model using uncertain criteria, normally used as a supplement to more common calibration procedures. These criteria include estimates of flood peaks, baseflow, recession and saturated area. It is shown that combinations of these criteria provide a powerful means of constraining the parameter space and reducing the simulation uncertainty. The second approach to model conditioning for ungauged basins uses an alternative method of regionalization that focuses on the estimation of flow characteristics rather than model parameter values. Strong relationships between flow characteristics (such as runoff coefficients, flow duration curves and coefficient of variation) and catchment conditions (such as area, mean annual rainfall and evaporation) are identified for catchments across Australia. Using the estimated ranges of these flow characteristics as assessment criteria, a rainfall-runoff model is successfully conditioned to adequately reproduce the streamflow response of the four test catchments. In particular it is shown that the use of numerous characteristics in tandem further improves the conditioning for the test catchments.

Research Doctorate - Doctor of Philosophy (PhD) / The purpose of rainfall-runoff modelling, like all environmental modelling is to generate simulations that accurately mimic those encountered in the system being modelled. Once this is achieved, the model may then be used to study the catchment response under conditions that have not previously been observed, such as the determination of extreme flood levels. The complex behaviour of the processes involved in the generation of streamflow mean that to achieve a usable model, simplifications must be made. This inevitably leads to the introduction of model error into the simulations, as these simplifications cannot reproduce the level of response variation encountered in a natural system. As a consequence, a model that performs well at some times may be inappropriate at other times. The MultiModel approach is an alternative method of rainfall-runoff modelling that uses numerous alternative process descriptions to generate a suite of unique rainfall runoff models. These models are calibrated and applied to allow for simulation responses that incorporate not only parameter variability but model structure variability. It is shown that the application of the MultiModel method to four test catchments produced simulated confidence limits that are much more likely to contain flood peaks that are beyond the range encountered during the calibration process than using a single model. This is due to the wider confidence limits generated as a result of the greater structure variability available to the MultiModel. The wider confidence limits are therefore a better reflection of our true understanding of the system being modelled. The prediction of ungauged basins presents an additional challenge to rainfallrunoff modelling. Most methods involve some form of regionalization of model parameters. These approaches are very limited in that they are restricted by model selection and application range. Two unique methods for the prediction of ungauged basins are presented that overcome these restrictions. The first attempts to condition a rainfall-runoff model using uncertain criteria, normally used as a supplement to more common calibration procedures. These criteria include estimates of flood peaks, baseflow, recession and saturated area. It is shown that combinations of these criteria provide a powerful means of constraining the parameter space and reducing the simulation uncertainty. The second approach to model conditioning for ungauged basins uses an alternative method of regionalization that focuses on the estimation of flow characteristics rather than model parameter values. Strong relationships between flow characteristics (such as runoff coefficients, flow duration curves and coefficient of variation) and catchment conditions (such as area, mean annual rainfall and evaporation) are identified for catchments across Australia. Using the estimated ranges of these flow characteristics as assessment criteria, a rainfall-runoff model is successfully conditioned to adequately reproduce the streamflow response of the four test catchments. In particular it is shown that the use of numerous characteristics in tandem further improves the conditioning for the test catchments.