This diploma thesis examines various linear regression methods and their use to establish regression relationships between the compressive strength of concrete determined by the indirect method and by the crushing of the specimens in the press. It deals mainly with the uncertainty of values measured by the indirect method, which is neglected by the usually used ordinary least squares regression method. It also deals with the weighted least squares method, suitable for so-called heteroskedastic data. It compares different regression methods on several sets of previously measured data. The final part of the work examines the effect of removing too influential points identified by Cook's distance, which may skew the regression results.

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Det finns olika aspekter som påverkar den ekonomiska tillväxten, där ibland inflation. Det har under många år pågått diskussioner om hur förhållandet mellan dessa två variabler ser ut. Denna uppsats analyserar sambandet mellan ekonomisk tillväxt och inflation. Utöver detta besvarar studien om inflation har någon statistisk signifikant relation till den ekonomiska tillväxten. I studien används paneldata från 19 OECD-medlemsländer från 1976 till 2020. För att analysera data utformas en regressionsmodell genom att använda BNP per capita som beroende variabel samt inkludera sju oberoende variabler (inflation, utländska direktinvesteringar, inhemska sparande, bytesvillkor, befolkningstillväxt, humankapital samt initial BNP). Resultatet från regressionsanalysen som utfördes genom fixed effects least squares dummy variable modellen tyder på ett negativt samband mellan inflation och BNP per capita. Däremot är resultatet enbart statistiskt signifikant om inte länder-, perioddummies eller initial BNP inkluderas. / There are various aspects that affect economic growth, including inflation. For many years, there have been discussions about the relationship between these two variables. This thesis analyzes the relation between economic growth and inflation. In addition, the study answers whether inflation has any statistically significant relation to economic growth. The study uses panel data from 19 OECD member countries from 1976 to 2020. To analyze the data, a regression model is designed by using ln GDP per capita as a dependent variable and including seven independent variables (inflation, foreign direct investment, domestic savings, terms of trade, population growth, human capital and initial GDP). The results of the regression analysis are conducted using the fixed effects least squares dummy variable model indicate a negative relationship between inflation and GDP per capita. However, the result is only shown to be statistically significant unless countries-, period dummies or initial GDP are included.

Markets increase social welfare by matching willing buyers and sellers. It is important to understand whether markets are fulfilling their societal purpose and are operating efficiently. The prevalence of spatial arbitrage in markets is an important indicator of market efficiency. The two essays in my dissertation study spatial arbitrage and the behaviors of arbitrageurs Electronic commerce can improve market efficiency by helping buyers and sellers find and transact with each other across geographic distance. In the first essay, we study the effect of two distinct forms of electronic commerce on market efficiency, which we measure via the prevalence of spatial arbitrage. Spatial arbitrage is a more precise measure than price dispersion, which is typically used, because it accounts for the transaction costs of trading across distance and for unobserved product heterogeneity. Studying two forms of electronic commerce allows us to examine how the theoretical mechanisms of expanded reach and transaction immediacy affect market efficiency. We find that electronic commerce reduces the number of arbitrage opportunities but improves arbitrageur’s ability to identify and exploit those that remain. Overall, our results provide a novel and nuanced understanding of how electronic commerce improves market efficiency. Studying arbitrageur strategies will help us understand how arbitrageur behaviors impact markets by increasing/reducing spatial arbitrage. In the second essay, we study specialization strategies of arbitrageurs. Arbitrageurs specialize on asset type and sourcing locations. We investigate the role of specialization and find that specialization affects both arbitrage profits and arbitrage intensity. Subsequently, we find that specialization strategies evolve over time and different groups of arbitrageurs adapt differently based on behavioral biases and environmental factors. Overall, our findings support the predictions of the adaptive markets hypothesis and help us understand antecedents such as capital, arbitrage intensity, etc. which affect the evolution of arbitrageur strategy.

Master of Science / Department of Statistics / Paul I. Nelson / The principle of least squares applied to regression models estimates parameters by minimizing the mean of squared residuals. Least squares estimators are optimal under normality but can perform poorly in the presence of outliers. This well known lack of robustness motivated the development of alternatives, such as least median of squares estimators obtained by minimizing the median of squared residuals. This report uses simulation to examine and compare the robustness of least median of squares estimators and least squares estimators of the slope of a regression line through the origin in terms of bias and mean squared error in a variety of conditions containing outliers created by using mixtures of normal and heavy tailed distributions. It is found that least median of squares estimation is almost as good as least squares estimation under normality and can be much better in the presence of outliers.

The primary aim of the research project presented in this thesis was to develop and test a comprehensive psychological model of interaction experience with news Web sites. Although news media have been publishing on the Web increasingly since the second half of the 1990s and news sites have become a favoured source of news for many, there is a lack of knowledge about news sites in terms of interaction-experience constructs and their structural relationships. The project aimed to examine people’s use of news sites from the perspective of interaction-experience research by developing a model and, based on this model, to provide guidance for designers of news sites. The project comprises three research phases: (1) exploratory phase, (2) modelling phase and (3) experimental phase. In the exploratory phase, a review of literature and an exploratory study of interaction experience with news Web sites were conducted. The latter explored how users of a particular news site interact with the site and which aspects of their experience they report. Data for the exploratory study were collected with an online questionnaire and by recording participants’ use of a news site under think-aloud instructions. In the modelling phase, an online questionnaire was used to collect answers to psychometric scales that were selected based on the literature review and the exploratory study. A measurement model was formulated to test the relationship between measurement items and the measurement scales, and structural models were formulated to test hypotheses related to the structural relationships of variables. Following the test results, a model of interaction experience with news sites was formulated to predict outcome measures of interaction experience from variables measuring aspects of interaction experience. Components of interaction experience, in turn, were predicted from measures of perceived news-site characteristics. In the experimental phase, an experiment was conducted to test the model of interaction experience with news sites in a controlled setting. Additionally, measures of person- and context characteristics were included in the prediction of components of interaction experience. The model of interaction experience with news sites was supported and accounted for a medium to substantial amount of variance in outcome measures. Finally, design guidance was derived from the model to advance interaction-experience knowledge, and conclusions were drawn regarding the model, in relation to existing research.

This dissertation consists of two chapters. The first chapter establishes an algorithm for calculating capital requirements. The calculation of capital requirements for financial institutions usually entails a reevaluation of the company's assets and liabilities at some future point in time for a (large) number of stochastic forecasts of economic and firm-specific variables. The complexity of this nested valuation problem leads many companies to struggle with the implementation. The current chapter proposes and analyzes a novel approach to this computational problem based on least-squares regression and Monte Carlo simulations. Our approach is motivated by a well-known method for pricing non-European derivatives. We study convergence of the algorithm and analyze the resulting estimate for practically important risk measures. Moreover, we address the problem of how to choose the regressors, and show that an optimal choice is given by the left singular functions of the corresponding valuation operator. Our numerical examples demonstrate that the algorithm can produce accurate results at relatively low computational costs, particularly when relying on the optimal basis functions. The second chapter discusses another application of regression-based methods, in the context of pricing variable annuities. Advanced life insurance products with exercise-dependent financial guarantees present challenging problems in view of pricing and risk management. In particular, due to the complexity of the guarantees and since practical valuation frameworks include a variety of stochastic risk factors, conventional methods that are based on the discretization of the underlying (Markov) state space may not be feasible. As a practical alternative, this chapter explores the applicability of Least-Squares Monte Carlo (LSM) methods familiar from American option pricing in this context. Unlike previous literature we consider optionality beyond surrendering the contract, where we focus on popular withdrawal benefits - so-called GMWBs - within Variable Annuities. We introduce different LSM variants, particularly the regression-now and regression-later approaches, and explore their viability and potential pitfalls. We commence our numerical analysis in a basic Black-Scholes framework, where we compare the LSM results to those from a discretization approach. We then extend the model to include various relevant risk factors and compare the results to those from the basic framework.

Lean system has drawn the attention of researchers and practitioners since its emergence in 1950s. This has been reflected by the increasing number of companies attempting to implement its practices and the large number of researchers investigating its effectiveness and identifying important contextual factors which affect its implementation. The rising level of interest in lean system has led to the emergence of three distinctive streams of literature. The first stream of literature has focused on the effectiveness of lean system. However, this literature was limited as it mainly examined the additive impact of lean practices on operational performance in the manufacturing context. The second stream of literature has focused on the role the accounting system in the lean context. In this body of literature, there was an agreement among researchers on the superiority of activity-based costing system (ABC) over the traditional accounting system in supporting the implementation of lean practices. However, most studies in this strand of literature were either conceptual or case-based studies. The third stream of literature has focused on the fit between business strategy and lean system. However, inconclusive results were reported in relation to the suitability of lean system to firms adopting the differentiation strategy and others adopting the cost leadership strategy. The aim of this study is to develop and empirically test a conceptual model which integrates the three distinctive streams of literature to extend their focus and overcome their limitations. More specifically, the model developed in the current study highlights not only the additive impact of lean practices but also the possible synergy among those practices in improving both operational and financial performance of service firms. In addition, the model brings to light the potential intervening role of ABC in the strategy-lean association. After identifying and reviewing the relevant literature, the socio-technical system theory and contingency theory were used to develop the conceptual model and associated hypotheses. A questionnaire instrument was designed to collect empirical data which was supplemented by objective data from the Financial Analysis Made Easy database in order to empirically test the conceptual model using partial least squares structural equation modelling (PLS-SEM). The findings of this study indicated that while the technical practices of lean service improved only the operational performance of service firms, the social practices enhanced both operational and financial performance. In addition, the two sets of practices positively interacted to improve firm performance over and above the improvement achieved from each set separately. Moreover, ABC was found to have a positive association with lean practice, and consequently an indirect positive relation with firm operational performance. Finally, both the differentiation and cost leadership strategy had a direct positive relationship with lean practices. However, while ABC was found to partially mediate the differentiation-lean association, it suppressed the cost leadership-lean association leading to a case of inconsistent mediation. The current study contributes to the current literature at different levels. First, at the theoretical level, this study develops a conceptual framework which crosses different streams of literatures mainly, lean system literature, management accounting literature (with focus on ABC), and business strategy literature. Unlike previous studies, by integrating the perspective of socio-technical system theory and contingency theory, the model (i) highlights not only the additive but also the synergistic effect of lean service practices on firm performance, (ii) brings to light the direct impact of ABC and business strategy on lean service practices and the intervening role of ABC due to which the business strategy is assumed to have also an indirect influence on lean practices, and (iii) offers an alternative view on how ABC can improve firm performance by enhancing other organisational capabilities (lean practices) which are expected to improve performance . Second, at the methodological level, unlike previous studies, this study includes a large number of lean service practices and contextual variables to report more precisely on the lean-performance association. In addition, the inclusion of the financial performance dimension-measured by secondary data- in the model besides the operational performance is critical to understand the full capability of lean service in improving firm performance. Further, employing a powerful statistical technique (PLS-SEM) provides more credibility to the results reported in this study. Third, at the empirical level, this study is conducted in the UK service sector. As such, this study is one of the very few studies that have reported on lean service and examined how the adoption of ABC and a specific type of business strategy can affect its implementation using empirical survey data from this context.

In this dissertation, we focus on solving Nonlinear Least Squares problems using a supervised approach. In particular, we developed a Supervised Descent Method (SDM), performed thorough theoretical analysis, and demonstrated its effectiveness on optimizing analytic functions, and four other real-world applications: Inverse Kinematics, Rigid Tracking, Face Alignment (frontal and multi-view), and 3D Object Pose Estimation. In Rigid Tracking, SDM was able to take advantage of more robust features, such as, HoG and SIFT. Those non-differentiable image features were out of consideration of previous work because they relied on gradient-based methods for optimization. In Inverse Kinematics where we minimize a non-convex function, SDM achieved significantly better convergence than gradient-based approaches. In Face Alignment, SDM achieved state-of-the-arts results. Moreover, it was extremely computationally efficient, which makes it applicable for many mobile applications. In addition, we provided a unified view of several popular methods including SDM on sequential prediction, and reformulated them as a sequence of function compositions. Finally, we suggested some future research directions on SDM and sequential prediction.