La recherche développée dans le cadre de cette thèse aborde différents aspects relevant de l’analyse statistique de données. Dans un premier temps, une analyse de trois indices d’associations entre deux tableaux de données est développée. Par la suite, des stratégies d’analyse liées à la standardisation de tableaux de données avec des applications en analyse en composantes principales (ACP) et en régression, notamment la régression PLS sont présentées. La première stratégie consiste à proposer une standardisation continuum des variables. Une standardisation plus générale est aussi abordée consistant à réduire de manière graduelle non seulement les variances des variables mais également les corrélations entre ces variables. De là, une approche continuum de régression a été élaborée regroupant l’analyse des redondances et la régression PLS. Par ailleurs, cette dernière standardisation a inspiré une démarche de régression biaisée dans le cadre de régression linéaire multiple. Les propriétés d’une telle démarche sont étudiées et les résultats sont comparés à ceux de la régression Ridge. Dans le cadre de l’analyse de plusieurs tableaux de données, une extension de la méthode ComDim pour la situation de K+1 tableaux est développée. Les propriétés de cette méthode, appelée P-ComDim, sont étudiées et comparées à celles de Multiblock PLS. Enfin, la situation où il s’agit d’évaluer l’effet de plusieurs facteurs sur des données multivariées est considérée et une nouvelle stratégie d’analyse est proposée. / The research developed in this thesis deals with several statistical aspects for analyzing datasets. Firstly, investigations of the properties of several association indices commonly used by practitioners are undergone. Secondly, different strategies related to the standardization of the datasets with application to principal component analysis (PCA) and regression, especially PLS-regression were developed. The first strategy consists of a continuum standardization of the variables. The interest of such standardization in PCA and PLS-regression is emphasized.A more general standardization is also discussed which consists in reducing gradually not only the variances of the variables but also their correlations. Thereafter, a continuum approach was developed combining Redundancy Analysis and PLS-regression. Moreover, this new standardization inspired a biased regression model in multiple linear regression. Properties related to this approach are studied and the results are compared on the basis of case studies with those of Ridge regression. In the context of the analysis of several datasets in an exploratory perspective, the method called ComDim, has certainly raised interest among practitioners. An extension of this method for the analysis of K+1 datasets was developed. Properties related to this method, called P-ComDim, are studied and compared to Multiblock PLS. Finally, for the analysis of datasets depending on several factors, a new approach based on PLS regression is proposed.

La thématique générale des travaux de la thèse porte sur l’utilisation des Technologies de l’information et de la communication afin de promouvoir l’activité physique et limiter les troubles dus à la sédentarité. Ils s’inscrivent dans le cadre d’un projet qui vise à développer une solution d’évaluation de la motricité des sujets humains à faible coût, en utilisant des capteurs inertiels embarqués. L’objectif du présent travail de thèse est d’évaluer les capacités posturales au travers deux exercices de Yoga. En premier lieu, nous avons validé l’utilisation des dispositifs BodyTrack, par rapport à un système de référence (Plateforme de force), dans le cadre de l’évaluation des oscillations posturales. Ensuite, une méthodologie est proposée afin d’évaluer la performance motrice selon 3 facteurs. Le premier considère le maintien de l’équilibre postural lors des phases statique des deux exercices. Le deuxième facteur évalue la durée de ces phases statiques et le troisième permet de vérifier la bonne exécution de la posture. L’ensemble des facteurs mesurés permet de construire une vue d’ensemble de l’exercice effectué et rend compte de la performance motrice. / Balance is a key element for daily activities, that’s making balance training, is important for ev eryone. In the aim of promoting physical activity and changing exercise behaviour, BodyScoring’s balance application, using an inexpensive mobile device provided with accelerometers, gyroscope and magnetometer, proposes tow Yoga exercises (‘Tadasana and Vrksasana’), for balance improvement, an d calculates a score to determine the level skills and share it with friends. First, this thesis examines th e validity, reliability and the sensitivity of accelerometer data by comparing them to force platform data. Second, a postural scoring system is developed. Based on three key factors, it allows evaluating the postural performance, the duration and the appropriate execution of the exercise. The graphical re presentation of the score has allowed a straightforward and simple interpretation of results.

A growing recognition of the need for effective marine environmental management as a result of the increasing exploitation of marine biological resources has highlighted the need for high speed ecological seabed mapping. The practice of mapping making extensive use of satellite remote sensing and airborne platforms is well established for terrestrial management. Marine biological resource mapping however is not readily available except in part from that derived for surface waters from satellite based ocean colour mapping. Perhaps the most fundamental reason is that of sampling difficulty, which involves broad areas of seabed coverage, irregularities of seabed surface and depth. Conventional grab sample techniques are widely accepted as a standard seabed mapping methodology that has been in use long before the advent of acoustic techniques and continue to be employed. However. they are both slow and labour intensive, factors which severely limit the spatial coverage available from practical grab sampling programs. While acoustic techniques have been used for some time in pelagic biomass assessment, only recently have acoustic techniques been applied to marine biological resource mapping of benthic communities. Two commercial bottom classifiers available in the market that use normal incidence echosounders are the RoxAnn and QTC View systems. Users and practitioners should be cautious however when using black box implementations of the two commercial systems without a proper quality control over raw acoustic data since some researchers in their studies have indicated problems with these two bottom classifiers such as, among others, a depth dependence. In this thesis, an alternative approach was adopted to the use of echosounder returns for bottom classification. / The approach used in this study is similar to,~ used in the commercial RoxAnn system. In grouping bottom types however, Multivariate analysis (Principal Component Analysis and Cluster Analysis) was adopted instead of the allocation system normally used in the RoxAnn system, called RoxAnn squares. In addition, the adopted approach allowed for quality control over acoustic data before further analysis was undertaken. As a working hypothesis, it was assumed that on average 0 and aE2 = 0 where E1 and E2 are the roughness and hardness indices, respectively, and RO is the depth. For roughness index (E1), this was achieved by introducing a constant angular integration interval to the tail of the first OM returns whereas for hardness index (E2), this was achieved by introducing a constant depth integration interval. Since three different frequencies, i.e. 12, 38 and kHz, were operated, Principal Component Analysis was used here to reduce the dimensionality of roughness and hardness indices, formed from the three operated qu frequencies separately. The k-means technique was applied to the first principal component of roughness index and the first principal comp component of hardness index to produce separable seabed types. This produced four separable seabed types, namely soft-smooth, soft-rough, hard-smooth and hard-rough seabeds. / Principal Component Analysis was also used to reduce the dimensionality of the area backscattering coefficient sA, a relative measure of biomass of benthic mobile biota. The bottom classification results reported here appear to be robust in that, where independent ground truthing was available, acoustic classification was generally congruent with ground truth results. When investigating the relationship between derived bottom type and acoustically assessed total biomass of benthic mobile biota, no trend linking the two parameters, however, appears. Nevertheless, using the hierarchical agglomerative technique applied to a set of variables containing average first principal component of the area backscattering coefficient sA, the average first principal component of roughness and hardness indices, the centroids of first principal component of roughness and hardness indices associated with the four seabed types and species composition of fish group of the common species in trawl stations available, two main groups of quasi acoustic population are observed in the North West Shelf (NWS) study area and three groups are observed in the South East Fisheries (SEF) study area. The two main groups of quasi acoustic population in the NWS study area and the three main groups of quasi acoustic population in the study area are associated with the derived seabed types and fish groups of the common species.

傳統的主成分分析(principal component analysis)法，只能分析二式二向的資料(2-mode 2-way data)，若是要處裡三向三式的資料(3-mode 3-way data)或是更多維的資料，則必須用其它的方法。例如將某一向資料取平均數，再做分析。此法雖然可行，但卻忽略三向資料間可能潛藏的相關性。且社會科學的研究日趨複雜，三向資料也就更常見到，而我們可能也對三向資料間彼此的關聯感到興趣。因此在1960、1970年代，學者開始研究將主成分分析的模型加以擴展成適合分析三向資料的模型。本文除了介紹三向資料主成分分析所使用的Tucker3模型及其參數估計法外，也以28家股票上市公司為實例，探討資本結構影響因素於五年間（1989~1993年）在不同公司群組間的變化情形。

In this work the two experimental dental implant materials FAT and FAW, made of fluoroapatite particles embedded in polymer matrices, and films of the proteins lysozyme, amylase and bovine serum albumin (BSA), adsorbed to the two dental implant materials, were investigated with time-of-flight secondary ion mass spectrometry (ToF-SIMS) and the multivariate data analysis technique discriminant principal component analysis (DPCA).

<p>This thesis grew out of a problem encountered by a subsidiary of a Swedish multinational industrial corporation. This subsidiary is responsible for the corporation’s customer financing activities. In the thesis, we refer to these entities as the Division and the Corporation. The Division needed to find a new approach to finance its customer loan portfolio. Risk control and return maximization were important aspects of this need. The objective of this thesis is to devise and implement a method that allows the Division to make optimal funding decisions, given a certain risk limit. </p><p>We propose a funding approach based on stochastic programming. Our approach allows the Division’s portfolio manager to minimize the funding costs while hedging against market risk. We employ principal component analysis and Monte Carlo simulation to develop a multicurrency scenario generation model for interest and exchange rates. Market rate scenarios are used as input to three different optimization models. Each of the optimization models presents the optimal funding decision as positions in a unique set of financial instruments. By choosing between the optimization models, the portfolio manager can decide which financial instruments he wants to use to fund the loan portfolio. </p><p>To validate our models, we perform empirical tests on historical market data. Our results show that our optimization models have the potential to deliver sound and profitable funding decisions. In particular, we conclude that the utilization of one of our optimization models would have resulted in an increase in the Division’s net income over the past 3.5 years.</p>

<p>The present thesis proposes new methods for obtaining objective and accurate diagnoses in modern healthcare. Non-invasive techniques have been used to examine or diagnose three different medical conditions, namely neuropathy among diabetics, radiotherapy induced erythema (skin redness) among breast cancer patients and diagnoses of cutaneous malignant melanoma. The techniques used were Near-InfraRed spectroscopy (NIR), Multi Frequency Bio Impedance Analysis of whole body (MFBIA-body), Laser Doppler Imaging (LDI) and Digital Colour Photography (DCP).</p><p>The neuropathy for diabetics was studied in papers I and II. The first study was performed on diabetics and control subjects of both genders. A separation was seen between males and females and therefore the data had to be divided in order to obtain good models. NIR spectroscopy was shown to be a viable technique for measuring neuropathy once the division according to gender was made. The second study on diabetics, where MFBIA-body was added to the analysis, was performed on males exclusively. Principal component analysis showed that healthy reference subjects tend to separate from diabetics. Also, diabetics with severe neuropathy separate from persons less affected.</p><p>The preliminary study presented in paper III was performed on breast cancer patients in order to investigate if NIR, LDI and DCP were able to detect radiotherapy induced erythema. The promising results in the preliminary study motivated a new and larger study. This study, presented in papers IV and V, intended to investigate the measurement techniques further but also to examine the effect that two different skin lotions, Essex and Aloe vera have on the development of erythema. The Wilcoxon signed rank sum test showed that DCP and NIR could detect erythema, which is developed during one week of radiation treatment. LDI was able to detect erythema developed during two weeks of treatment. None of the techniques could detect any differences between the two lotions regarding the development of erythema.</p><p>The use of NIR to diagnose cutaneous malignant melanoma is presented as unpublished results in this thesis. This study gave promising but inconclusive results. NIR could be of interest for future development of instrumentation for diagnosis of skin cancer.</p>

<p> </p><p>The today quarry planning at Klinthagen is rough, which provides an opportunity to introduce new exciting methods to improve the quarry gain and efficiency. Nordkalk AB, active at Klinthagen, wishes to start a new quarry at a nearby location. To exploit future quarries in an efficient manner and ensure production quality, multivariate statistics may help gather important information.</p><p>In this thesis the possibilities of the multivariate statistical approaches of Principal Component Analysis (PCA) and Partial Least Squares (PLS) regression were evaluated on the Klinthagen bore data. PCA data were spatially interpolated by Kriging, which also was evaluated and compared to IDW interpolation.</p><p>Principal component analysis supplied an overview of the variables relations, but also visualised the problems involved when linking geophysical data to geochemical data and the inaccuracy introduced by lacking data quality.</p><p>The PLS regression further emphasised the geochemical-geophysical problems, but also showed good precision when applied to strictly geochemical data.</p><p>Spatial interpolation by Kriging did not result in significantly better approximations than the less complex control interpolation by IDW.</p><p>In order to improve the information content of the data when modelled by PCA, a more discrete sampling method would be advisable. The data quality may cause trouble, though with sample technique of today it was considered to be of less consequence.</p><p>Faced with a single geophysical component to be predicted from chemical variables further geophysical data need to complement existing data to achieve satisfying PLS models.</p><p>The stratified rock composure caused trouble when spatially interpolated. Further investigations should be performed to develop more suitable interpolation techniques.</p>

<p>The principle purpose of this thesis has been to study and analyse the conception of men and women in business bankruptcy during the 20th century. The analysis is built on a theoretical gender perspective and, combining this view and business and bankruptcy research, the thesis has focused on five themes: business networks, bank contacts, business competence, business characteristics and finally bankruptcy causes. These themes have been in focus when analysing bankruptcies in Uppsala 1920-1939, 1988, 1992 and 1996. A questionnair- and interview study with receivers active in Sweden 2001 has also been carried out. From the bankruptcy cases that have been studied, no specific gender differences have really been discovered. There were some variations between men and women, but it is very hard to claim that these are related to the sex of the debtor more than to the branch or to the individuals. Changes from the inter-war period to the latter part of the 20th century are in these respects also small. The image that the receivers gave through the questionnaire and interview study indicates on the other hand that there existed a conception that men and women seemed different as business owners. It is obvious that there were many receivers who thought that women were different from men in a situation of business bankruptcy, even though several of them stated that they did not beleive in any gender differences.</p>

The collection and interpretation of data is a critical component of traffic and transportation engineering used to establish baseline performance measures and to forecast future conditions. One important source of traffic data is commercial motor vehicle (CMV) weight and classification data used as input to critical tasks in transportation design, operations, and planning. The evolution of Intelligent Transportation System (ITS) technologies has been providing transportation engineers and planners with an increased availability of CMV data. The primary sources of these data are automatic vehicle classification (AVC) and weigh-in-motion (WIM). Microscopic traffic simulation models have been used extensively to model the dynamic and stochastic nature of transportation systems including vehicle composition. One aspect of effective microscopic traffic simulation models that has received increased attention in recent years is the calibration of these models, which has traditionally been concerned with identifying the "best" parameter set from a range of acceptable values. Recent research has begun the process of automating the calibration process in an effort to accurately reflect the components of the transportation system being analyzed. The objective of this research is to develop a methodology in which the effects of CMVs can be included in the calibration of microscopic traffic simulation models. The research examines the ITS data available on weight and operating characteristics of CMVs and incorporates this data in the calibration of microscopic traffic simulation models. The research develops a methodology to model CMVs using microscopic traffic simulation models and then utilizes the output of these models to generate the data necessary to quantify the impacts of CMVs on infrastructure, travel time, and emissions. The research uses advanced statistical tools including principal component analysis (PCA) and recursive partitioning to identify relationships between data collection sites (i.e., WIM, AVC) such that the data collected at WIM sites can be utilized to estimate weight and length distributions at AVC sites. The research also examines methodologies to include the distribution or measures of central tendency and dispersion (i.e., mean, variance) into the calibration process. The approach is applied using the CORSIM model and calibrated utilizing an automated genetic algorithm methodology.