<p> </p><p>The world is experiencing yet another energy- and fuel predicament as oil prices are escalating to new hights. Alternative fuels are being promoted globally as the increasing gasoline prices trigger inflation. Basic food commodities are some of the goods hit by this inflation and the purpose of this thesis is to analyse whether the higher maize and sugar prices are having any effect on the expanding ethanol production. This thesis focuses on the two major crop inputs in ethanol production: maize (in the US) and sugar cane (in Brazil). Econometric tests using cross-sectional data were carried through to find the elasticities of the variables. The crops prices were tested against ethanol output using the log-linear model in several regressions to find a relationship. In addition, the output levels of the crops were tested using the same method. It was found that maize prices and output affects ethanol production. Sugar cane prices do not have any significant impact on ethanol production while sugar cane output has a small, yet significant relationhip with ethanol. Consequently, ethanol’s rise in the fuel market could be a result of increased maize input, rather than sugar.</p><p> </p> / <p>Dagens värld upplever ännu ett energi- och bränsle predikament när oljepriser eskalerar mot nya höjder. Alternativa bränslen marknadsförs globalt samtidigt som de stigande bensinpriserna stimulerar inflationen. Några av de varor som drabbas av denna inflation är grundläggande livsmedelsprodukter och syftet med denna uppsats är att analysera huruvida de högre priserna på majs och socker påverkar den expanderande etanolproduktionen. Uppsatsen fokuserar på de två stora grödor som används som insatsvaror vid framställningen av etanol: majs (i USA) och sockerrör (i Brasilien). Ekonometriska tester genomfördes för att erhålla variablernas elasticiteter med hjälp av den cross-sectional data som behandlades. Genom log-linear modellen utfördes det ett antal regressioner för att hitta ett samband mellan grödornas priser och etanolproduktionen. Därutöver genomfördes tester för att hitta sambandet mellan grödornas utbud och etanol med hjälp av samma modell. Det upptäcktes att både pris och utbudet av majs påverkar etanolproduktionen. Sockerrörspriser har ingen signifikant inverkan på etanolproduktionen medan utbudet av sockerrör har en signifikant, om än svag, relation till etanol. Följaktligen kan etanols tillväxt i  bränslemarknaden tolkas som ett resultat av en stigande majsinsats snarare än sockerinstats vid etanolframställningen.</p>

<p>Financial stock market data, for various reasons, frequently contain missing values. One reason for this is that, because the markets close for holidays, daily stock prices are not always observed. This creates gaps in information, making it difficult to predict the following day’s stock prices. In this situation, information during the holiday can be “borrowed” from other countries’ stock market, since global stock prices tend to show similar movements and are in fact highly correlated. The main goal of this study is to combine stock index data from various markets around the world and develop an algorithm to impute the missing values in individual stock index using “information-sharing” between different time series. To develop imputation algorithm that accommodate time series-specific features, we take multiple imputation approach using dynamic linear model for time-series and panel data. This algorithm assumes ignorable missing data mechanism, as which missingness due to holiday. The posterior distributions of parameters, including missing values, is simulated using Monte Carlo Markov Chain (MCMC) methods and estimates from sets of draws are then combined using Rubin’s combination rule, rendering final inference of the data set. Specifically, we use the Gibbs sampler and Forward Filtering and Backward Sampling (FFBS) to simulate joint posterior distribution and posterior predictive distribution of latent variables and other parameters. A simulation study is conducted to check the validity and the performance of the algorithm using two error-based measurements: Root Mean Square Error (RMSE), and Normalized Root Mean Square Error (NRMSE). We compared the overall trend of imputed time series with complete data set, and inspected the in-sample predictability of the algorithm using Last Value Carried Forward (LVCF) method as a bench mark. The algorithm is applied to real stock price index data from US, Japan, Hong Kong, UK and Germany. From both of the simulation and the application, we concluded that the imputation algorithm performs well enough to achieve our original goal, predicting the stock price for the opening price after a holiday, outperforming the benchmark method. We believe this multiple imputation algorithm can be used in many applications that deal with time series with missing values such as financial and economic data and biomedical data.</p> / Thesis

Πολλά είναι τα προβλήματα που καλούμαστε να αντιμετωπίσουμε στην καθημερινότητά μας, και που χρίζουν την ανάγκη προσδιορισμού αυτών, μέσω του Γραμμικού Στοχαστικού Προγραμματισμού. Βασικό εργαλείο των προβλημάτων του Γραμμικού Στοχαστικού Προγραμματισμού που χρησιμοποιείται για την υπολογιστική τους επίλυση είναι οι μέθοδοι του Γραμμικού και του Μη Γραμμικού Προγραμματισμού. Στο 1ο κεφάλαιο της παρούσας Διπλωματικής Εργασίας, υπενθυμίζονται οι βασικές ιδιότητες και μέθοδοι επίλυσης των Γραμμικών και Μη Γραμμικών προβλημάτων, όπως αυτές χρησιμοποιούνται από τον Στοχαστικό Προγραμματισμό. Στο 2ο κεφάλαιο, παρουσιάζεται μια σειρά από Γραμμικά μοντέλα Στοχαστικού Γραμμικού Προγραμματισμού ενός σταδίου συζητώντας τις θεωρητικές τους ιδιότητες, σχετικές με την υπολογιστική τους δυνατότητα, μία από τις οποίες αποτελεί η κυρτότητά τους. Στο 3ο, και τελευταίο κεφάλαιο, ακολουθείται μια αντίστοιχη παρουσίαση των Γραμμικών Στοχαστικών μοντέλων πολλαπλών σταδίων, τονίζοντας τις ιδιότητες αυτές που επιτρέπουν την κατασκευή προσεγγιστικών μεθόδων επίλυσης. / There are various special problem formulations to be dealt with in our daily life, and our conclusion is that a basic toolkit of Linear and Nonlinear Programming methods cannot be waived if we want to deal with the computational solution of Stochastic Linear Programming problems. In chapter 1, basic properties of Linear Problems and Non Linear Problems, as well as their solution methods, are reminded, as they are used in the Stochastic Linear Programming. In chapter 2, various Single-stage Stochastic Linear Programming (SLP) models are presented and their theoretical properties are discussed, which are relevant for their computational tractability, as convexity statements. Conclusions are presented in chapter 3, followed by an analogous discussion of Multi-stage SLP models, focussed, among others, on properties allowing for the construction of particular approximation methods for computing solutions.

In practice there is a long tradition of actuaries calculating reserve estimates according to deterministic methods without explicit reference to a stochastic model. For instance, the chain-ladder was originally a deterministic reserving method. Moreover, the actuaries often make ad hoc adjustments of the methods, for example, smoothing of the chain-ladder development factors, in order to fit the data set under analysis. However, stochastic models are needed in order to assess the variability of the claims reserve. The standard statistical approach would be to first specify a model, then find an estimate of the outstanding claims under that model, typically by maximum likelihood, and finally the model could be used to find the precision of the estimate. As a compromise between this approach and the actuary's way of working without reference to a model the object of the research area has often been to first construct a model and a method that produces the actuary's estimate and then use this model in order to assess the uncertainty of the estimate. A drawback of this approach is that the suggested models have been constructed to give a measure of the precision of the reserve estimate without the possibility of changing the estimate itself. The starting point of this thesis is the inconsistency between the deterministic approaches used in practice and the stochastic ones suggested in the literature. On one hand, the purpose of Paper I is to develop a bootstrap technique which easily enables the actuary to use other development factor methods than the pure chain-ladder relying on as few model assumptions as possible. This bootstrap technique is then extended and applied to the separation method in Paper II. On the other hand, the purpose of Paper III is to create a stochastic framework which imitates the ad hoc deterministic smoothing of chain-ladder development factors which is frequently used in practice.

It is an important step in clinical practice to discriminate real diseased patients from healthy persons. It would be great to get such discrimination from some common information like personal information, life style, and the contact with diseased patient. In this study, a score is calculated for each patient based on a survey through generalized linear model, and then the diseased status is decided according to previous sexually transmitted diseases (STDs) records. This study will facilitate clinics in grouping patients into real diseased or healthy, which in turn will affect the method clinics take to screen patients: complete screening for possible diseased patient and some common screening for potentially healthy persons.

Multivariate generalized linear mixed models (MGLMM) are used for jointly modeling the clustered mixed outcomes obtained when there are two or more responses repeatedly measured on each individual in scientific studies. The relationship among these responses is often of interest. In the clustered mixed data, the correlation could be present between repeated measurements either within the same observer or between different observers on the same subjects. This study proposes a series of in- dices, namely, intra, inter and total correlation coefficients, to measure the correlation under various circumstances of observations from a multivariate generalized linear model, especially for joint modeling of clustered count and continuous outcomes. Bayesian methods are widely used techniques for analyzing MGLMM. The need for noninformative priors arises when there is insufficient prior information on the model parameters. Another aim of this study is to propose an approximate uniform shrinkage prior for the random effect variance components in the Bayesian analysis for the MGLMM. This prior is an extension of the approximate uniform shrinkage prior. This prior is easy to apply and is shown to possess several nice properties. The methods are illustrated in terms of both a simulation study and a case example.

Quasi-keyhole, including plasma keyhole and double-sided welding, is a novel approach proposed to operate the keyhole arc welding process. It can result in a high quality weld, but also raise higher demand of the operator. A computer control system to detect the keyhole and control the arc current can improve the performance of the welding process. To this effect, developing automatic pipe welding, instead of manual welding, is a hot research topic in the welding field. The objective of this research is to design an automatic quasi-keyhole pipe welding system that can monitor the keyhole and control its establishment time to track the reference trajectory as the dynamic behavior of welding processes changes. For this reason, an automatic plasma welding system is proposed, in which an additional electrode is added on the back side of the workpiece to detect the keyhole, as well as to provide the double-side arc in the double-sided arc welding mode. In the automatic pipe welding system the arc current can be controlled by the computer controller. Based on the designed automatic plasma pipe welding system, two kinds of model predictive controller − linear and bilinear − are developed, and an optimal algorithm is designed to optimize the keyhole weld process. The result of the proposed approach has been verified by using both linear and bilinear model structures in the quasi-keyhole plasma welding (QKPW) process experiments, both in normal plasma keyhole and double-sided arc welding modes.

With data describing 110,520 eighth grade students from 592 junior high (middle) schools in China, a three-level hierarchical linear model was developed in this study to create a multivariate multilevel environment to examine (a) the effects of student-level and school-level variables on science achievement in four subject areas (science inquiry skills, biology, earth science, and physics) and (b) the consistency or stability of academic achievement across the four subject areas among students and among schools. Results indicated that (a) student characteristics, including gender, parental SES, time spent in learning, and the type of family separation, were related to high academic achievement in each of the four science subject areas, (b) no school characteristics were found to be significant factors to affect students’ academic performance in any of the four science subject areas, (c) both students and schools with high academic achievement in one subject area also showed high academic achievement in other subject areas, and (d) the consistency or stability of science performance over the four subject areas did not depend on student characteristics and school characteristics.

Cattails (Typha spp.) are invasive and tend to decrease the biodiversity and area of open water of marshes, particularly where the natural hydrological cycles have been altered, as in Delta Marsh, Manitoba. Understanding the distribution of T. latifolia L., T. angustifolia L., their hybrid, T. x glauca Godr., and the environmental variables associated with their habitats, may give valuable insight for managing cattails. The distribution of these cattail species and hybrid were surveyed in 2011 in prairie pothole and roadside ditch marshes across southwestern Manitoba and southeastern Saskatchewan. Plants were identified by analysis of microscopic leaf-lamina margin characteristics. T. x glauca was most widespread, followed by T. latifolia, whereas T. angustifolia was rare and only found as far west as central Manitoba. Current understanding of the correlations between cattail invasions and their environment is conflicting and largely based on lacustrine wetland studies. A generalized linear model was developed. The model explained approximately 40% of the variation in T. x glauca distribution in the prairie potholes and ditches. The model included the environmental variables of sediment Olsen-P, sediment nitrate-N, water pH, litter depth, surrounding land use, and the interaction between Olsen-P and nitrate-N. Olsen-P was the most important of these variables, because its removal from the model significantly reduced the residual deviance of the model (P=0.05). In a survey of 13 transects throughout Delta Marsh in 2009, hybrid cattail, T. x glauca, was dominant, T. angustifolia was rare, and T. latifolia was absent. ANOVA linear regression (P=0.05) revealed that above-ground biomass was correlated with mean cattail ramet height, cattail ramet density, and standing litter biomass. Cattail ramet density was negatively correlated with sampling date and positively correlated with standing litter biomass. Mean cattail height was correlated with fallen litter biomass. One-way ANOVA (P=0.05) revealed that fallen litter biomass was lowest in quadrats closer to the open water, and mean cattail height was greatest at the quadrats closest to the open water. While mean cattail height differed depending on whether the cattail stand was a hybrid monoculture or a mixed stand of T. x glauca and T. angustifolia, no other cattail population variables were correlated with stand type. As revealed by one-way ANOVA (P=0.05), water conductivity, sediment texture, total-N, nitrate-N, Olsen-P, and organic-C were not important variables in the distributions of T. x glauca or T. angustifolia at Delta Marsh. Therefore, managing the nutrient levels at Delta Marsh would not likely be important for limiting the distribution of the cattails at this marsh. However, reducing the P concentration in pothole and ditch marshes may limit cattails in those environments.

This dissertation develops influence diagnostics for crossover models. Mixed linear models and generalised mixed linear models are utilised to investigate continuous and count data from crossover studies, respectively. For both types of models, changes in the maximum likelihood estimates of parameters, particularly in the estimated treatment effect, due to minor perturbations of the observed data, are assessed. The novelty of this dissertation lies in the analytical derivation of influence diagnostics using decompositions of the perturbed mixed models. Consequently, the suggested influence diagnostics, referred to as the delta-beta and variance-ratio influences, provide new findings about how the constructed residuals affect the estimation in terms of different parameters of interest. The delta-beta and variance-ratio influence in three different crossover models are studied in Chapters 5-6, respectively. Chapter 5 analyses the influence of subjects in a two-period continuous crossover model. Possible problems with observation-level perturbations in crossover models are discussed. Chapter 6 extends the approach to higher-order crossover models. Furthermore, not only the individual delta-beta and variance-ratio influences of a subject are derived, but also the joint influences of two subjects from different sequences. Chapters 5-6 show that the delta-beta and variance-ratio influences of a particular parameter are decided by the special linear combination of the constructed residuals. In Chapter 7, explicit delta-beta influence on the estimated treatment effect in the two-period count crossover model is derived. The influence is related to the Pearson residuals of the subject. Graphical tools are developed to visualise information of influence concerning crossover models for both continuous and count data. Illustrative examples are provided in each chapter.