In data-driven network and systems engineering, we often train models offline using measurement data collected from networks. Offline learning achieves good results but has drawbacks. For example, model training incurs a high computational cost and the training process takes a long time. In this project, we follow an online approach for model training. The approach involves a cache of fixed size to store measurement samples and recomputation of ML models based on the current cache. Key to this approach are sample selection algorithms that decide which samples are stored in the cache and which are evicted. We implement three sample selection methods in this project: reservoir sampling, maximum entropy sampling and maximum coverage sampling. In the context of sample selection methods, we evaluate model recomputation methods to control when to retrain the model using the samples in the current cache and use the retrained model to predict the following samples before the next recomputation moment. We compare three recomputation strategies: no recomputation, periodic recomputation and recomputation using the ADWIN algorithm. We evaluate the three sample selection methods on five datasets. One of them is the FedCSIS 2020 Challenge dataset and the other four are KTH testbed datasets. We find that maximum entropy sampling can achieve quite good performance compared to other sample selection methods and that recomputation using the ADWIN algorithm can help reduce the number of recomputations and does not affect the prediction performance. / Vid utveckling och underhåll av datornätverk och system så används ofta maskininlärningsmodeller (ML) som beräknats offline med datavärden som insamlats från nätverket. Att beräkna ML-modeller offline ger bra resultat men har nackdelar. Beräkning av ML-modeller är tidskrävande och medför en hög beräkningskostnad. I detta projekt undersöker vi en metod för att beräkna ML-modeller online. Metoden använder en cache av fixerad storlek för att lagra mätningsvärden och omberäknar ML-modeller baserat på innehållet i cachen. Nyckeln till denna metod är användandet av urvalsalgoritmer som avgör vilka mätningsvärden som ska lagras i cachen och vilka som ska tas bort. Vi tillämpar tre urvalsmetoder: urval baserat på en behållare av fixerad storlek, urval baserat på maximal entropi, samt urval baserat på maximal täckning. Vid användning av urvalsmetoder så utvärderar vi metoder för att avgöra när en ML-modell ska omberäknas baserat på urvalet i cachen. Den omberäknade ML-modellen används sedan för att göra prediktioner tills dess att modellen omberäknas igen. Vi utvärderar tre strategier för att avgöra när en modell ska omberäknas: ingen omberäkning, periodisk omberäkning, samt omberäkning baserat på ADWIN-algoritmen. Vi utvärderar tre urvalsmetoder på fem olika datauppsättningar. En av datauppsättningarna är baserat på FedCSIS 2020 Challenge och de andra fyra datauppsättningarna har insamlats från en testbädd på KTH. Vi _nner att urval baserat på maximal entropi uppnår bra prestanda jämfört med de andra urvalsmetoderna samt att en omberäkningstrategi baserat på ADWIN-algoritmen kan minska antalet omberäkningar och försämrar inte prediktionsprestandan.

Cette thèse de doctorat examine les principales défaillances du marché du travail qui entraînent que les travailleurs n’arrivent pas à obtenir la pleine rémunération potentielle qui corresponde à leur capital humain. Il y a « inefficacité salariale » lorsque le salaire obtenu est inférieur au maximum atteignable. Dans un tel cas, les salariés reçoivent un salaire injuste par rapport au capital humain disposé. Cela décourage à investir dans son capital humain ce qui aura tendance à réduire la productivité totale, à affaiblir la compétitivité et à nuire à la croissance économique du pays. La contribution que nous apportons à travers ce travail est de trois ordres. Dans un premier temps, nous proposons un nouveau regard par rapport à l’intégration des jeunes sur le marché du travail. Plutôt que d’examiner si les individus obtiennent un contrat de travail stable ou non, nous adoptons une approche qui s’intéresse à la qualité de l’appariement « emploi – compétences » de jeunes entrant fraîchement dans la vie active. Nos travaux fournissent des résultats empiriques qui mettent en évidence les différentes théories de recherche d’emploi. Dans un second temps, en raison du considérable défi que représente l'identification et l'évaluation des pratiques discriminatoires sur le marché du travail, nous proposons une approche innovatrice et efficace pour examiner le phénomène du plafond de verre (barrière invisible à l’accès des postes de décision mieux rémunérés). Dans la dernière partie de cette thèse, nous proposons un modèle économétrique théorique qui améliore la correction du problème de biais de sélection pour les modèles de frontière stochastique. / This doctoral thesis addresses issues related to employees’ imperfect information on the labour market and discrimination, generally all direct consequences of labour underpayment or “earnings inefficiency”. Workers are in a situation of earnings inefficiency when they do not receive the full potential remuneration corresponding to their human capital endowment: unfair pay for greater stock of human capital. This situation is problematic from a policy-makers point of view as it could weaken work incentives, discourage investments in human capital, and harm economic growth and competitiveness. It could also widen inequality within the society and contribute to the increase in relative poverty.The contribution we make through this work is threefold. First, we examine the integration of young people into the labour market from a new angle. Instead of examining whether individuals obtain stable employment or not, we use an approach that focuses on the quality of the job matching for young people entering the workforce and lacking labour market information. This first chapter provides empirical evidence on job search theories. In a second chapter, because of the considerable challenge of identifying and assessing discriminatory practices in the labour market, we propose an innovative and effective approach to examine the phenomenon of the glass ceiling (an invisible barrier to management positions associated with higher earnings). Finally, the last part of this doctoral thesis is devoted to improving the econometric approach we use. We propose a theoretical econometric model that improves correction for sample selection bias with stochastic frontier models.

No description available.

La plupart des maladies humaines ont une étiologie complexe avec des facteurs génétiques et environnementaux qui interagissent. Utiliser des phénotypes corrélés peut augmenter la puissance de détection de locus de trait quantitatif. Ce travail propose d’évaluer différentes approches d’analyse bivariée pour des traits corrélés en utilisantl’information apportée par les marqueurs au niveau de la liaison et de l’association. Legain relatif de ces approches est comparé aux analyses univariées. Ce travail a étéappliqué à la variation de la densité osseuse à deux sites squelettiques dans une cohorted’hommes sélectionnés pour des valeurs phénotypiques extrêmes. Nos résultats montrentl’intérêt d’utiliser des approches bivariées en particulier pour l’analyse d’association. Parailleurs, dans le cadre du groupe de travail GAW16, nous avons comparé lesperformances relatives de trois méthodes d’association dans des données familiales. / The majority of complex diseases in humans are likely determined by both genetic andenvironmental factors. Using correlated phenotypes may increase the power to map theunderlying Quantitative Trait Loci (QTLs). This work aims to evaluate and compare theperformance of bivariate methods for detecting QTLs in correlated phenotypes by linkageand association analyses. We applied these methods to data on Bone Mineral Density(BMD) variation, measured at the two skeletal sites, in a sample of males selected forextreme trait values. Our results demonstrate the relative gain, in particular for associationanalysis, of bivariate approaches when compared to univariate analyses. Finally, we studythe performances of association methods to detect QTLs in the GAW16 simulated familydata.

The United States cheese consumption has grown considerably over the years. Using Nielsen Homescan panel data for calendar years 2005 and 2006, this dissertation examines the effect of economic and socio-demographic factors on the demand for disaggregated cheese varieties and on the cheese industry in general. In the first essay, we estimated the censored demand for 14 cheese varieties and identified the respective own-price and cross-price elasticities. Also, non-price factors were determined affecting the purchase of each variety as well as the impact of generic dairy advertising. Results revealed that most of the natural cheese varieties have an elastic demand while the processed cheese products exhibited inelastic demands. Strong substitution and complementarity relationships were identified as well, and a two quarter carry-over effect of advertising was observed for most of cheese demands. Results also showed that household demographics affected the demands differently, depending on the nature of the cheese varieties. The second essay examined the impact of retail promotion on the decision to purchase private label processed cheese products using a probit model. A strong negative relationship was found between national brand manufacturer couponing activity and the private label purchase decision. Therefore, national brand couponing appears to be an effective strategy for manufacturers to deter private label growth. This analysis also shows that the decision of purchasing a private label cheese product is influenced by socio-demographic characteristics of the household, namely household income and size, age and education level of the household head, race, ethnicity, and location. In the third study, the feasibility of fortifying processed cheese with omega-3 is investigated. This ex-ante analysis took into account the market conditions and evaluates the increase in the demand for processed cheese needed to offset the costs of fortification in order to maintain the profitability of manufacturers like Kraft. Initially, the censored demand for processed cheese products is estimated using panel data; subsequently, the profitability of manufacturing such product is determined.This analysis shows that, within reasonable market conditions and reasonable marginal costs, the fortification of processed cheese products with omega-3 fatty acids indeed is feasible from a profitability standpoint to manufacturers.

In the present doctoral thesis, we estimated Mincer's (1974) semi logarithmic wage function for the French and Pakistani labour force data. This model is considered as a standard tool in order to estimate the relationship between earnings/wages and different contributory factors. Despite of its vide and extensive use, simple estimation of the Mincerian model is biased because of different econometric problems. The main sources of bias noted in the literature are endogeneity of schooling, measurement error, and sample selectivity. We have tackled the endogeneity and measurement error biases via instrumental variables two stage least squares approach for which we have proposed two new instrumental variables. The first instrumental variable is defined as "the average years of schooling in the family of the concerned individual" and the second instrumental variable is defined as "the average years of schooling in the country, of particular age group, of particular gender, at the particular time when an individual had joined the labour force". Schooling is found to be endogenous for the both countries. Comparing two said instruments we have selected second instrument to be more appropriate. We have applied the Heckman (1979) two-step procedure to eliminate possible sample selection bias which found to be significantly positive for the both countries which means that in the both countries, people who decided not to participate in labour force as wage worker would have earned less than participants if they had decided to work as wage earner. We have estimated a specification that tackled endogeneity and sample selectivity problems together as we found in respect to present literature relative scarcity of such studies all over the globe in general and absence of such studies for France and Pakistan, in particular. Differences in coefficients proved worth of such specification. We have also estimated model semi-parametrically, but contrary to general norm in the context of the Mincerian model, our semi-parametric estimation contained non-parametric component from first-stage schooling equation instead of non-parametric component from selection equation. For both countries, we have found parametric model to be more appropriate. We found errors to be heteroscedastic for the data from both countries and then applied adaptive estimation to control adverse effects of heteroscedasticity. Comparing simple and adaptive estimations, we prefer adaptive specification of parametric model for both countries. Finally, we have applied quantile regression on the selected model from mean regression. Quantile regression exposed that different explanatory factors influence differently in different parts of the wage distribution of the two countries. For both Pakistan and France, it would be the first study that corrected both sample selectivity and endogeneity in single specification in quantile regression framework

No description available.

No description available.

Dans cette thèse, notre cadre d’analyse repose sur l’estimation de la fonction de gain proposée par Mincer (1974). Le but est de reprendre la spécification de ce modèle en s'intéressant aux problèmes d’estimation liés. Le but est aussi une comparaison pour les marchés du travail français et pakistanais en utilisant une spécification plus robuste.[...] Toutefois, suivant une nombreuse littérature, la simple estimation du modèle de Mincer est biaisée, ceci en raison de différents problèmes. [...] Dans la présente thèse deux nouvelles variables instrumentales sont proposées dans une application de type IV2SLS. [...] D'après l'analyse menée dans cette thèse, la seconde variable instrumentale apparaît être la plus appropriée, cela puisqu’elle possède un faible effet direct sur la variable de réponse par rapport à la première variable instrumentale proposée. Par ailleurs, la définition de cette variable instrumentale est plus robuste que la première variable instrumentale. [...] Pour éliminer une autre source potentielle de biais, dans l'estimation du modèle de Mincer, i.e. le biais de sélection, la classique méthode à deux étapes de correction proposée par Heckman (1979) a été appliquée. Par cette méthode le biais de sélection a été trouvé positif et statistiquement significatif pour les deux pays. [...] Dans la littérature relative à l'estimation du modèle de Mincer, nous avons noté qu’il y a très peu d'études qui corrigent les deux sources de biais simultanément et aucune étude de cette nature n’existe pas pour la France ou le Pakistan.[...] Donc, en réponse, nous estimons ici une seule spécification corrigeant de manière simultanée le biais de sélection de l'échantillon et le biais d'endogénéité de l'éducation. Nous avons également noté, toujours d'après la littérature, que la robustesse des hypothèses du modèle linéaire utilisé pour estimer le modèle de Mincer a rarement été discutée et testée.[...] Nous avons donc testé formellement la validité de l'hypothèse d'homoscédasticité, cela en appliquant le test de White (1980).[...] Donc, afin d'éviter les effets de l'hétéroscédasticité des erreurs sur le processus d'estimation, nous avons réalisé une estimation adaptative du modèle de Mincer.[...]Basées sur la performance globale des modèles paramétrique et semi-paramétrique, nous avons constaté que, pour la France, les deux formes d'estimation apparaissent bien spécifiées. Toujours dans l'idée de maintenir la facilité d’estimation, le modèle paramétrique a été sélectionné afin d'être le plus approprié pour les données françaises. Pour l'analyse du Pakistan, nous avons conclu que le modèle semi-paramétrique produit des résultats en désaccord avec l’agrément général au Pakistan, mais aussi en rapport à la littérature internationale pour certaines des variables.[...] Donc, comme pour les données françaises, pour les données pakistanaises, nous avons aussi choisi le modèle paramétrique comme le plus robuste qu’afin d'estimer les impacts exercés par les différents facteurs explicatifs sur le processus de la détermination des salaires. Pour les deux pays, après avoir comparé les versions simples et adaptatives du modèle paramétrique et du modèle semi-paramétrique, nous avons trouvé que le modèle paramétrique dans la spécification adaptative est plus performant dans l’objectif d'estimer les impacts des différents facteurs contributifs au processus de détermination des salaires.Enfin, nous avons estimé le modèle de Mincer dans une forme paramétrique choisie de ces estimations, comme le plus approprié en rapport à la forme semi-paramétrique, et à partir de l'analyse de régression en moyenne, comme pour le modèle de régression par quantile.[...]La méthode de régression par quantile a révélé que la plupart des variables explicatives influencent les gains salariaux, ceci différemment suivant les différentes parties de la distribution des salaires, pour les deux marchés du travail considérés. / In the present doctoral thesis, we estimated Mincer’s (1974) semi logarithmic wage function for the French and Pakistani labour force data. This model is considered as a standard tool in order to estimate the relationship between earnings/wages and different contributory factors. Despite of its vide and extensive use, simple estimation of the Mincerian model is biased because of different econometric problems. The main sources of bias noted in the literature are endogeneity of schooling, measurement error, and sample selectivity. We have tackled the endogeneity and measurement error biases via instrumental variables two stage least squares approach for which we have proposed two new instrumental variables. The first instrumental variable is defined as "the average years of schooling in the family of the concerned individual" and the second instrumental variable is defined as "the average years of schooling in the country, of particular age group, of particular gender, at the particular time when an individual had joined the labour force". Schooling is found to be endogenous for the both countries. Comparing two said instruments we have selected second instrument to be more appropriate. We have applied the Heckman (1979) two-step procedure to eliminate possible sample selection bias which found to be significantly positive for the both countries which means that in the both countries, people who decided not to participate in labour force as wage worker would have earned less than participants if they had decided to work as wage earner. We have estimated a specification that tackled endogeneity and sample selectivity problems together as we found in respect to present literature relative scarcity of such studies all over the globe in general and absence of such studies for France and Pakistan, in particular. Differences in coefficients proved worth of such specification. We have also estimated model semi-parametrically, but contrary to general norm in the context of the Mincerian model, our semi-parametric estimation contained non-parametric component from first-stage schooling equation instead of non-parametric component from selection equation. For both countries, we have found parametric model to be more appropriate. We found errors to be heteroscedastic for the data from both countries and then applied adaptive estimation to control adverse effects of heteroscedasticity. Comparing simple and adaptive estimations, we prefer adaptive specification of parametric model for both countries. Finally, we have applied quantile regression on the selected model from mean regression. Quantile regression exposed that different explanatory factors influence differently in different parts of the wage distribution of the two countries. For both Pakistan and France, it would be the first study that corrected both sample selectivity and endogeneity in single specification in quantile regression framework

Magister Commercii (Industrial Psychology) - MCom(IPS) / The focus of this exploratory study was on competency profile development, specifically the factors impacting on the validity of its development. Given the paucity of research both nationally and internationally into the development of criteria feeding employment practices, as well as the conjectured enigmatic disjuncture between theory, which promotes the almost indispensability of job analysis, and organisational reality which attests to it seldom being performed or performed in a way which would satisfy scientific standards, a qualitative enquiry and a two tiered research design was developed to explore this phenomenon. Through excavating documentary data, the first phase of research intensively explored the work of the City of Cape Town's Competency Framework Team, their particular job analysis processes and their methodology for developing a competency profile for a single incumbent position, namely that of the City Manager's position. The medium of the case study allowed the reader to enter the world of a pulsing organisation and witness such researchers' dilemmas as contemplating whether there is a standard recipe for competency profile generation, the factors influencing choice of methodology, judgment around the relevancy of competencies developed to lead the change process, accurately responding to and managing dramatically skewed samples, the types of interventions to design, etc. The three key results from this phase of research confirmed that: the complexity of change within the City of Cape Town, as well as the types of decisions the various HR functions had to make on the basis of the profile, influenced decisions on how to profile and which methods to use; that stakeholders actively shaped the design and understanding of the particular components of the competency profile as they bring human volition to the areas of challenge arising within the organisation; and on the issue of whether racial composition of a sample was anticipated to have an effect on the competencies generated, it was clear that is not possible to ascertain whether the differences noticed in the behavioural repertoire of an individual are as a function of race or a myriad of other competing variables. The second phase of research studied the behavioural competencies elicited from a sample of Chief Executive Officers when using different job analysis methods to develop these competencies. The results confirmed that the distinctive features of a job analysis method selected or developed may impact on the behavioural competencies generated. These results not only sensitise practitioners to the role of methodology in influencing the derivation of competencies, but also to the many variables within, as well as between chosen methodologies, and to the reality that choice of methodology may influence the degree of confidence with which one interprets the results attained. The study concluded that despite this being a case study, limiting the conclusiveness and generalisability of its findings, the facets of the phenomenon of competency profiling illuminated may have much salience for the art and practice of profiling in general, for users and developers of job analysis processes, instruments, and leadership models, as well as practitioners entrusted with organisational design and redesign.