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This Ph.D. thesis concerns the problem of assessing distributional properties in multivariate regression models with possibly related marginal models. Such models are of great importance in most branches of statistics. The four papers in this thesis deal with different distributional aspects of relevance for all models. Paper 1 concerns the problem of assessing normality in the multivariate regression model. Paper 2 concerns the problem of assessing normality in situations when the data is heteroscedastic or autocorrelated. Paper 3 concerns testing for heteroscedasticity in linear regression models. Paper 4 presents four different types of tests for autocorrelation to be used in SUR models or multivariate regressions.
This is a Ph.D. dissertation. The need for statistical surveillance has been noticed in many different areas. Examples of applications discussed in this thesis include the detection of an increased incidence of a disease and the detection of intra-uterine
This is a Ph.D. dissertation. Statistical surveillance is used to repeatedly evaluate the amount of information contained in observations which are achieved continuously. This makes it possible to quickly and safely detect changes in the way economic and financial time series evolve through time. Thus, the optimal time for decisions can be determined. The thesis treats systems for early warnings of turns in economic processes. In papers I & II it is demonstrated how such systems can be used to predict the turning points of the general business cycle, by detecting turns in leading indicators. In papers III & IV some strategies for timely transactions in the financial market are analyzed by means of the theory of statistical surveillance.
"This is a Ph.D. dissertation. Longitudinal analysis is important when individual effects are present. In this thesis some methods for different kinds of inference on longitudinal data are derived and evaluated in small sample settings. Appropriate evaluation criteria are determined from the actual inferential situation. It is based on three papers: ""Maximum Likelihood Ratio Based Small-Sample Tests for Random Coefficients in Linear Regression"", ""Preliminary Testing in a Class of Simple Non-Linear Mixed Models to Improve Estimation Accuracy"" and ""Detection of Intra-Uterine Growth Restriction""."
This volume contains the papers from the Sixth Eugene Lukacs Symposium on ''Multidimensional Statistical Analysis and Random Matrices'', which was held at the Bowling Green State University, Ohio, USA, 29--30 March 1996. Multidimensional statistical analysis and random matrices have been the topics of great research. The papers presented in this volume discuss many varied aspects of this all-encompassing topic. In particular, topics covered include generalized statistical analysis, elliptically contoured distribution, covariance structure analysis, metric scaling, detection of outliers, density approximation, and circulant and band random matrices.
Quick Ethnography (QE) is an easy-to-read guide to the rapid collection of high quality ethnographic data for use in research, policy analysis, and decision-making. It addresses the needs of social scientists grappling with complex cultural social interactions and cultural change occurring in communities around the globe by offering a comprehensive, integrated multi-method approach that will increase research productivity. Handwerker provides step-by-step procedures for producing lots of data very quickly, outlining how ethnographers must control field preparation, data collection, and methods of data analysis. The rigorous QE approach allows greater precision and subtlety of ethnographic description and explanation that is not always possible in applied contract work (known as Rapid Assessment Procedures). The author, an anthropologist who has been teaching and consulting on fieldwork methods for over 25 years, includes extensive examples of research design and management that are valuable for the novice as well as for experienced researchers in all social science disciplines. Visit the author's web site.
This book provides an essential overview of the basic principles of imaging modalities, accompanied by examples of their applications in modern clinical and associated pre-clinical studies. The monograph is based on the original results of investigation of the efficiency use of laser light and Mueller-matrix polarimetry approach for assessment of myocardial tissues towards confirmation the cause of death. A morphological analysis of necrotic changes in the myocardial tissue of patients that died due to heart attack, coronary heart disease and acute coronary insufficiency was carried out and the data and histological sections of the myocardium inspected utilizing Mueller-matrix mapping of tissue samples with polarized light. A unified optical model of polycrystalline structure of the myocardium is proposed, and the principles and regulations of Mueller-matrix description of its polarization manifestations are explored and developed. The book also provides a statistical and scale-selective wavelet analysis of polarization and Mueller-matrix maps. Finally, the key forensic medical criteria for the differential diagnosis of the cause of death due to necrotic and pathological changes in the morphological structure of the myocardium have been established
A practical guide for multivariate statistical techniques-- nowupdated and revised In recent years, innovations in computer technology and statisticalmethodologies have dramatically altered the landscape ofmultivariate data analysis. This new edition of Methods forStatistical Data Analysis of Multivariate Observations explorescurrent multivariate concepts and techniques while retaining thesame practical focus of its predecessor. It integrates methods anddata-based interpretations relevant to multivariate analysis in away that addresses real-world problems arising in many areas ofinterest. Greatly revised and updated, this Second Edition provides helpfulexamples, graphical orientation, numerous illustrations, and anappendix detailing statistical software, including the S (or Splus)and SAS systems. It also offers * An expanded chapter on cluster analysis that covers advances inpattern recognition * New sections on inputs to clustering algorithms and aids forinterpreting the results of cluster analysis * An exploration of some new techniques of summarization andexposure * New graphical methods for assessing the separations among theeigenvalues of a correlation matrix and for comparing sets ofeigenvectors * Knowledge gained from advances in robust estimation anddistributional models that are slightly broader than themultivariate normal This Second Edition is invaluable for graduate students, appliedstatisticians, engineers, and scientists wishing to usemultivariate techniques in a variety of disciplines.
This book is a useful resource for government policy analysts, academics, students of higher education and business practitioners interested in African economies and the key economic issues these economies are facing in 2020. In the face of weak governance and growth globally, there is still a window of opportunity for countries in Africa to build on not only their traditional industrial capabilities, but also pave the way for positive developments in international trade and in the way governments tackle poverty and inequality. By focusing on four areas: (1) agriculture and livestock, (2) consumption, poverty and inequality, (3) financial services, employment and corporate governance, and (4) economic integration, international trade and foreign direct investment (FDI), this book presents a series of empirical studies that examine important contemporary economic issues facing Africa. The book incorporates a range of methodological approaches, with some chapters providing case study analyses while others embrace more traditional forms of econometric testing.