Inference on Cointegration in Vector Autoregressive Models (summary section only)

In the thesis we consider inference for cointegration in vector autoregressive (VAR) models. The thesis consists of an introduction and four papers. The first paper proposes a new test for cointegration in VAR models that is directly based on the eigenvalues of the least squares (LS) estimate of the autoregressive matrix. In the second paper we compare a small sample correction for the likelihood ratio (LR) test of cointegrating rank and the bootstrap. The simulation experiments show that the bootstrap works very well in practice and dominates the correction factor. The tests are applied to international stock prices data, and the .nite sample performance of the tests are investigated by simulating the data. The third paper studies the demand for money in Sweden 1970—2000 using the I(2) model. In the fourth paper we re-examine the evidence of cointegration between international stock prices. The paper shows that some of the previous empirical results can be explained by the small-sample bias and size distortion of Johansen’s LR tests for cointegration. In all papers we work with two data sets. The first data set is a Swedish money demand data set with observations on the money stock, the consumer price index, gross domestic product (GDP), the short-term interest rate and the long-term interest rate. The data are quarterly and the sample period is 1970(1)—2000(1). The second data set consists of month-end stock market index observations for Finland, France, Germany, Sweden, the United Kingdom and the United States from 1980(1) to 1997(2). Both data sets are typical of the sample sizes encountered in economic data, and the applications illustrate the usefulness of the models and tests discussed in the thesis.

Photophysics of conjugated polymers: interplay between Forster energy migration and defect concentration in shaping a photochemical funnel in PPV

Recent single molecule experiments have suggested the existence of a photochemical funnel in the photophysics of conjugated polymers, like poly[2-methoxy-5-(2'-ethylhexyl)oxy-1,4-phenylenevinylene] (MEH-PPV). The funnel is believed to be a consequence of the presence of conformational or chemical defects along the polymer chain and efficient non-radiative energy transfer among different chromophore segments. Here we address the effect of the excitation energy dynamics on the photophysics of PPV. The PPV chain is modeled as a polymer with the length distribution of chromophores given either by a Gaussian or by a Poisson distribution. We observe that the Poisson distribution of the segment lengths explains the photophysics of PPV better than the Gaussian distribution. A recently proposed version of an extended particle-in-a-box' model is used to calculate the exciton energies and the transition dipole moments of the chromophores, and a master equation to describe the excitation energy transfer among different chromophores. The rate of energy transfer is assumed to be given here, as a first approximation, by the well-known Forster expression. The observed excitation population dynamics confirms the photochemical funneling of excitation energy from shorter to longer chromophores of the polymer chain. The time scale of spectral shift and energy transfer for our model polymer, with realistic values of optical parameters, is in the range of 200-300 ps. We find that the excitation energy may not always migrate towards the longest chromophore segments in the polymer chain as the efficiency of energy transfer between chromophores depends on the separation distance between the two and their relative orientation.

An elastic-viscoplastic constitutive model for the hot-forming of aluminum alloys

Under hot-forming conditions characterized by high homologous temperatures and strain-rates, metals usually exhibit rate-dependent inelastic behavior. An elastic-viscoplastic constitutive model is presented here to describe metal behavior during hot-forming. The model uses an isotropic internal variable to represent the resistance offered to plastic deformation by the microstructure. Evolution equations are developed for the inelastic strain and the deformation resistance based on experimental results. A methodology is presented for extracting model parameters from constant true strain-rate compression tests performed at different temperatures. Model parameters are determined for an Al-1Mn alloy and an Al-Mg-Si alloy, and the predictions of the model are shown to be in good agreement with the experimental data. (C) 2000 Kluwer Academic Publishers.

The hard-particle model for a dense granular flow down an inclined plane

Perfectly hard particles are those which experience an infinite repulsive force when they overlap, and no force when they do not overlap. In the hard-particle model, the only static state is the isostatic state where the forces between particles are statically determinate. In the flowing state, the interactions between particles are instantaneous because the time of contact approaches zero in the limit of infinite particle stiffness. Here, we discuss the development of a hard particle model for a realistic granular flow down an inclined plane, and examine its utility for predicting the salient features both qualitatively and quantitatively. We first discuss Discrete Element simulations, that even very dense flows of sand or glass beads with volume fraction between 0.5 and 0.58 are in the rapid flow regime, due to the very high particle stiffness. An important length scale in the shear flow of inelastic particles is the `conduction length' delta = (d/(1 - e(2))(1/2)), where d is the particle diameter and e is the coefficient of restitution. When the macroscopic scale h (height of the flowing layer) is larger than the conduction length, the rates of shear production and inelastic dissipation are nearly equal in the bulk of the flow, while the rate of conduction of energy is O((delta/h)(2)) smaller than the rate of dissipation of energy. Energy conduction is important in boundary layers of thickness delta at the top and bottom. The flow in the boundary layer at the top and bottom is examined using asymptotic analysis. We derive an exact relationship showing that the a boundary layer solution exists only if the volume fraction in the bulk decreases as the angle of inclination is increased. In the opposite case, where the volume fraction increases as the angle of inclination is increased, there is no boundary layer solution. The boundary layer theory also provides us with a way of understanding the cessation of flow when at a given angle of inclination when the height of the layer is decreased below a value h(stop), which is a function of the angle of inclination. There is dissipation of energy due to particle collisions in the flow as well as due to particle collisions with the base, and the fraction of energy dissipation in the base increases as the thickness decreases. When the shear production in the flow cannot compensate for the additional energy drawn out of the flow due to the wall collisions, the temperature decreases to zero and the flow stops. Scaling relations can be derived for h(stop) as a function of angle of inclination.

Methods in general model localization

The aim of this study was to evaluate and test methods which could improve local estimates of a general model fitted to a large area. In the first three studies, the intention was to divide the study area into sub-areas that were as homogeneous as possible according to the residuals of the general model, and in the fourth study, the localization was based on the local neighbourhood. According to spatial autocorrelation (SA), points closer together in space are more likely to be similar than those that are farther apart. Local indicators of SA (LISAs) test the similarity of data clusters. A LISA was calculated for every observation in the dataset, and together with the spatial position and residual of the global model, the data were segmented using two different methods: classification and regression trees (CART) and the multiresolution segmentation algorithm (MS) of the eCognition software. The general model was then re-fitted (localized) to the formed sub-areas. In kriging, the SA is modelled with a variogram, and the spatial correlation is a function of the distance (and direction) between the observation and the point of calculation. A general trend is corrected with the residual information of the neighbourhood, whose size is controlled by the number of the nearest neighbours. Nearness is measured as Euclidian distance. With all methods, the root mean square errors (RMSEs) were lower, but with the methods that segmented the study area, the deviance in single localized RMSEs was wide. Therefore, an element capable of controlling the division or localization should be included in the segmentation-localization process. Kriging, on the other hand, provided stable estimates when the number of neighbours was sufficient (over 30), thus offering the best potential for further studies. Even CART could be combined with kriging or non-parametric methods, such as most similar neighbours (MSN).

Vapor phase oxidation of p-xylene

The kinetics of the vapor phase oxidation of p-xylene over ferric molybdate catalyst were studied in an isothermal, differential, tubular flow reactor in the temperature range of 360 to 420° C. The major product obtained was p-tolualdehyde with small amounts of maleic anhydride and p-toluic acid. No terephthalic acid or CO2 were observed. The reaction rate data collected fit the redox model given by Equation 1. The values of activation energies Ex, Eo and frequency factors Ax, Ao obtained are 72, 63 kJ/mol and 0.64, 2.89 m3/kg catalyst s respectively. The reaction mechanism was established by studying the oxidation of p-tolualdehyde, toluic and terephthalic acids. It is concluded that the reaction follows a parallel-consecutive scheme. On a étudié la cinétique de l'oxydation, en phase gazeuse, du para-xylène sur un catalyseur consistant en molybdate ferrique; cette oxydation s'est faite dans un réacteur à écoulement tubulaire, isothermique et différentiel, dans une échelle de températures comprises entre 360°C et 420°C. Le produit principal obtenu a été le para-tolualdéhyde; on a aussi trouvé de faibles quantités d'anhydride maléique et d'acide para-toluique, mais on n'a pas noté la présence d'acide téréphtalique ni d'anhydride carbonique (CO2). Les résultats obtenus en ce qui a trait à la vitesse de réaction concordent bien avec les données du modèle redox indiquées par l'équation 1. Les valeurs des énergies d'activation Ex et Eo ainsi que des facteurs de fréquence Ax et Ao obtenus sont respectivement 72 et 63 kilojoules/mol. et 0.64 × 103 et 2.89 m3/kg de catalyseur. On a établi le mécanisme de la réaction en étudiant l'oxydation du para-tolualdéhyde et des acides toluique et téréphtalique. On conclut que la réaction se fait d'une manière parallèle et consécutive.

Nonlinear mixture autoregressive model: economic applications

The aim of this dissertation is to model economic variables by a mixture autoregressive (MAR) model. The MAR model is a generalization of linear autoregressive (AR) model. The MAR -model consists of K linear autoregressive components. At any given point of time one of these autoregressive components is randomly selected to generate a new observation for the time series. The mixture probability can be constant over time or a direct function of a some observable variable. Many economic time series contain properties which cannot be described by linear and stationary time series models. A nonlinear autoregressive model such as MAR model can a plausible alternative in the case of these time series. In this dissertation the MAR model is used to model stock market bubbles and a relationship between inflation and the interest rate. In the case of the inflation rate we arrived at the MAR model where inflation process is less mean reverting in the case of high inflation than in the case of normal inflation. The interest rate move one-for-one with expected inflation. We use the data from the Livingston survey as a proxy for inflation expectations. We have found that survey inflation expectations are not perfectly rational. According to our results information stickiness play an important role in the expectation formation. We also found that survey participants have a tendency to underestimate inflation. A MAR model has also used to model stock market bubbles and crashes. This model has two regimes: the bubble regime and the error correction regime. In the error correction regime price depends on a fundamental factor, the price-dividend ratio, and in the bubble regime, price is independent of fundamentals. In this model a stock market crash is usually caused by a regime switch from a bubble regime to an error-correction regime. According to our empirical results bubbles are related to a low inflation. Our model also imply that bubbles have influences investment return distribution in both short and long run.

Estimating Frequencies of Minority Nevirapine-Resistant Strains in Chronically HIV-1-Infected Individuals Naive to Nevirapine by Using Stochastic Simulations and a Mathematical Model

Nevirapine forms the mainstay of our efforts to curtail the pediatric AIDS epidemic through prevention of mother-to-child transmission of HIV-1. A key limitation, however, is the rapid selection of HIV-1 strains resistant to nevirapine following the administration of a single dose. This rapid selection of resistance suggests that nevirapine-resistant strains preexist in HIV-1 patients and may adversely affect outcomes of treatment. The frequencies of nevirapine-resistant strains in vivo, however, remain poorly estimated, possibly because they exist as a minority below current assay detection limits. Here, we employ stochastic simulations and a mathematical model to estimate the frequencies of strains carrying different combinations of the common nevirapine resistance mutations K103N, V106A, Y181C, Y188C, and G190A in chronically infected HIV-1 patients naive to nevirapine. We estimate the relative fitness of mutant strains from an independent analysis of previous competitive growth assays. We predict that single mutants are likely to preexist in patients at frequencies (similar to 0.01% to 0.001%) near or below current assay detection limits (>0.01%), emphasizing the need for more-sensitive assays. The existence of double mutants is subject to large stochastic variations. Triple and higher mutants are predicted not to exist. Our estimates are robust to variations in the recombination rate, cellular superinfection frequency, and the effective population size. Thus, with 10(7) to 10(8) infected cells in HIV-1 patients, even when undetected, nevirapine-resistant genomes may exist in substantial numbers and compromise efforts to prevent mother-to-child transmission of HIV-1, accelerate the failure of subsequent antiretroviral treatments, and facilitate the transmission of drug resistance.

United We Stand - Divided We Fall : A Standard Model of Unit Cohesion

Research on unit cohesion has shown positive correlations between cohesion and valued outcomes such as strong performance, reduced stress, less indiscipline, and high re-enlistment intentions. However, the correlations have varied in strength and significance. The purpose of this study is to show that taking into consideration the multi-component nature of cohesion and relating the most applicable components to specific outcomes could resolve much of the inconsistency. Unit cohesion is understood as a process of social integration among members of a primary group with its leaders, and with the larger secondary groups of which they are a part. Correspondingly, included in the framework are four bonding components: horizontal (peer) and vertical (subordinate and leader) and organizational and institutional, respectively. The data were collected as part of a larger research project on cohesion, leadership, and personal adjustment to the military. In all, 1,534 conscripts responded to four questionnaires during their service in 2001-2002. In addition, sociometric questionnaires were given to 537 group members in 47 squads toward the end of their service. The results showed that platoons with strong primary-group cohesion differed from other platoons in terms of performance, training quality, secondary-group experiences, and attitudes toward refresher training. On the sociometric level it was found that soldiers who were chosen as friends by others were more likely to have higher expected performance, better performance ratings, more positive attitudes toward military service, higher levels of well-being during conscript service, and fewer exemptions from duty during it. On the group level, the selection of the respondents own group leader rather than naming a leader from outside (i.e., leader bonding) had a bearing not only on cohesion and performance, but also on the social, attitudinal, and behavioral criteria. Overall, the aim of the study was to contribute to the research on cohesion by introducing a model that takes into account the primary foci of bonding and their impact. The results imply that primary-group and secondary-group bonding processes are equally influential in explaining individual and group performance, whereas the secondary-group bonding components are far superior in explaining career intentions, personal growth, avoidance of duty, and attitudes toward refresher training and national defense. This should be considered in the planning and conducting of training. The main conclusion is that the different types of cohesion components have a unique, positive, significant, but varying impact on a wide range of criteria, confirming the need to match the components with the specific criteria.

Aspiration-based utility functions in a planning model for timber flow management.

The study presents a theory of utility models based on aspiration levels, as well as the application of this theory to the planning of timber flow economics. The first part of the study comprises a derivation of the utility-theoretic basis for the application of aspiration levels. Two basic models are dealt with: the additive and the multiplicative. Applied here solely for partial utility functions, aspiration and reservation levels are interpreted as defining piecewisely linear functions. The standpoint of the choices of the decision-maker is emphasized by the use of indifference curves. The second part of the study introduces a model for the management of timber flows. The model is based on the assumption that the decision-maker is willing to specify a shape of income flow which is different from that of the capital-theoretic optimum. The utility model comprises four aspiration-based compound utility functions. The theory and the flow model are tested numerically by computations covering three forest holdings. The results show that the additive model is sensitive even to slight changes in relative importances and aspiration levels. This applies particularly to nearly linear production possibility boundaries of monetary variables. The multiplicative model, on the other hand, is stable because it generates strictly convex indifference curves. Due to a higher marginal rate of substitution, the multiplicative model implies a stronger dependence on forest management than the additive function. For income trajectory optimization, a method utilizing an income trajectory index is more efficient than one based on the use of aspiration levels per management period. Smooth trajectories can be attained by squaring the deviations of the feasible trajectories from the desired one.

A rationalisation of fatigue thresholds in pearlitic steels using a theoretical model

From a detailed re-examination of results in the literature, the effects of microstructure sizes, namely interlamellar spacing, pearlitic colony size and the prior austentitic grain size on the thresholds for fatigue crack growth (ΔKth) and crack closure (Kcl, th) have been illustrated. It is shown that while interlamellar spacing explicitly controls yield strength, a similar effect on ΔKth cannot be expected. On the other hand, the pearlitic colony size is shown to strongly influence ΔKth and Kcl, th through the deflection and retardation of cracks at colony boundaries. Consequently, an increase in ΔKth and Kcl, th with colony size has been found. The development of a theoretical model to illustrate the effects of colony size, shear flow stress in the slip band and macroscopic yield strength on Kcl, th and ΔKth is presented. the model assumes colony boundaries as potential sites for slip band pile-up formation and subsequent crack deflection finally leading to zig-zag crack growth. Using the concepts of roughness induced crack closure, the magnitude of Kcl, th is quantified as a function of colony size. In deriving the model, the flow stress in the slip band has been considered to represent the work hardened state in pearlite. Comparison of the theoretically predicted trend with the experimental data demonstrates very good agreement. Further, the intrinsic or closure free component of the fatigue threshold, ΔKeff, th is found to be insensitive to colony size and interlamellar spacing. Using a criterion for intrinsic fatigue threshold which considers the attainment of a critical fracture stress over a characteristic distance corresponding to interlamellar spacing, ΔKth values at high R values can be estimated with reasonable accuracy. The magnitude of ΔKth as a function of colony size is then obtained by summing up the average value of experimentally obtained ΔKeff, th values and the predicted Kcl, th values as a function of colony size. Again, very good agreement of the theoretically predicted ΔKth values with those experimentally obtained has been demonstrated.

Infinite dimensional slow modulations in a well known delayed model for cutting tool vibrations

We apply the method of multiple scales (MMS) to a well-known model of regenerative cutting vibrations in the large delay regime. By ``large'' we mean the delay is much larger than the timescale of typical cutting tool oscillations. The MMS up to second order, recently developed for such systems, is applied here to study tool dynamics in the large delay regime. The second order analysis is found to be much more accurate than the first order analysis. Numerical integration of the MMS slow flow is much faster than for the original equation, yet shows excellent accuracy in that plotted solutions of moderate amplitudes are visually near-indistinguishable. The advantages of the present analysis are that infinite dimensional dynamics is retained in the slow flow, while the more usual center manifold reduction gives a planar phase space; lower-dimensional dynamical features, such as Hopf bifurcations and families of periodic solutions, are also captured by the MMS; the strong sensitivity of the slow modulation dynamics to small changes in parameter values, peculiar to such systems with large delays, is seen clearly; and though certain parameters are treated as small (or, reciprocally, large), the analysis is not restricted to infinitesimal distances from the Hopf bifurcation.

A model for antiferromagnetic to superconductor transition

A model system capable of exhibiting both superconductivity of conduction electrons and “antiferromagnetic” order of site localised electrons is studied. Coexistence of both types of order seems a possibility and the model predicts a re-entrant behaviour of the transition temperature.

Rate Control State-of-the-art Survey

The majority of Internet traffic use Transmission Control Protocol (TCP) as the transport level protocol. It provides a reliable ordered byte stream for the applications. However, applications such as live video streaming place an emphasis on timeliness over reliability. Also a smooth sending rate can be desirable over sharp changes in the sending rate. For these applications TCP is not necessarily suitable. Rate control attempts to address the demands of these applications. An important design feature in all rate control mechanisms is TCP friendliness. We should not negatively impact TCP performance since it is still the dominant protocol. Rate Control mechanisms are classified into two different mechanisms: window-based mechanisms and rate-based mechanisms. Window-based mechanisms increase their sending rate after a successful transfer of a window of packets similar to TCP. They typically decrease their sending rate sharply after a packet loss. Rate-based solutions control their sending rate in some other way. A large subset of rate-based solutions are called equation-based solutions. Equation-based solutions have a control equation which provides an allowed sending rate. Typically these rate-based solutions react slower to both packet losses and increases in available bandwidth making their sending rate smoother than that of window-based solutions. This report contains a survey of rate control mechanisms and a discussion of their relative strengths and weaknesses. A section is dedicated to a discussion on the enhancements in wireless environments. Another topic in the report is bandwidth estimation. Bandwidth estimation is divided into capacity estimation and available bandwidth estimation. We describe techniques that enable the calculation of a fair sending rate that can be used to create novel rate control mechanisms.

Radiative effects of aerosols at an urban location in southern India: Observations versus model

The radiative impact of aerosols is one of the largest sources of uncertainty in estimating anthropogenic climate perturbations. Here we have used independent ground-based radiometer measurements made simultaneously with comprehensive measurements of aerosol microphysical and optical properties at a highly populated urban site, Bangalore (13.02 degrees N, 77.6 degrees E) in southern India during a dedicated campaign during winter of 2004 and summer and pre-monsoon season of 2005. We have also used longer term measurements carried out at this site to present general features of aerosols over this region. The aerosol radiative impact assessments were made from direct measurements of ground reaching irradiance as well as by incorporating measured aerosol properties into a radiative transfer model. Large discrepancies were observed between measured and modeled (using radiative transfer models, which employed measured aerosol properties) radiative impacts. It appears that the presence of elevated aerosol layers and (or) inappropriate description of aerosol state of mixing are (is) responsible for the discrepancies. On a monthly scale reduction of surface irradiance due to the presence of aerosols (estimated using radiative flux measurements) varies from 30 to 65 W m(-2). The lowest values in surface radiative impact were observed during June when there is large reduction in aerosol as a consequence of monsoon rainfall. Large increase in aerosol-induced surface radiative impact was observed from winter to summer. Our investigations re-iterate the inadequacy of aerosol measurements at the surface alone and importance of representing column properties (using vertical profiles) accurately in order to assess aerosol-induced climate changes accurately. (C) 2010 Elsevier Ltd. All rights reserved.