Em ecologia, o comportamento dos animais é freqüentemente estudado para entender melhor suas preferências por diferentes tipos de alimento e habitat. O presente trabalho esta relacionado a este tópico, dividindo-se em três capítulos. O primeiro capitulo refere-se à estimação da função da probabilidade da seleção de recurso (RSPF) comparado com um modelo de escolha discreta (DCM) com uma escolha, usando as estatísticas qui-quadrado para obter as estimativas. As melhores estimativas foram obtidas pelo método DCM com uma escolha. No entanto, os animais não fazem a sua seleção baseados apenas em uma escolha. Com RSPF, as estimativas de máxima verossimilhança, usadas pela regressão logística ainda não atingiram os objetivos, já que os animais têm mais de uma escolha. R e o software Minitab e a linguagem de programação Fortran foram usados para obter os resultados deste capítulo. No segundo capítulo discutimos mais a verossimilhança do primeiro capítulo. Uma nova verossimilhança para a RSPF é apresentada, a qual considera as unidades usadas e não usadas, e métodos de bootstrapping paramétrico e não paramétrico são usados para estudar o viés e a variância dos estimadores dos parâmetros, usando o programa FORTRAN para obter os resultados. No terceiro capítulo, a nova verossimilhança apresentada no capítulo 2 é usada com um modelo de escolha discreta, para resolver parte do problema apresentado no primeiro capítulo. A estrutura de encaixe é proposta para modelar a seleção de habitat de 28 corujas manchadas (Strix occidentalis), assim como a uma generalização do modelo logit encaixado, usando a maximização da utilidade aleatória e a RSPF aleatória. Métodos de otimização numérica, e o sistema computacional SAS, são usados para estimar os parâmetros de estrutura de encaixe. / In ecology, the behavior of animals is often studied to better understand their preferences for different types of habitat and food. The present work is concerned with this topic. It is divided into three chapters. The first concerns the estimation of a resource selection probability function (RSPF) compared with a discrete choice model (DCM) using chi-squared to obtain estimates. The best estimates were obtained by the DCM method. Nevertheless, animals were not selected based on choice alone. With RSPF, the maximum likelihood estimates used with the logistic regression still did not reach the objectives, since the animals have more than one choice. R and Minitab software and the FORTRAN programming language were used for the computations in this chapter. The second chapter discusses further the likelihood presented in the first chapter. A new likelihood for a RSPF is presented, which takes into account the units used and not used, and parametric and non-parametric bootstrapping are employed to study the bias and variance of parameter estimators, using a FORTRAN program for the calculations. In the third chapter, the new likelihood presented in chapter 2, with a discrete choice model is used to resolve a part of the problem presented in the first chapter. A nested structure is proposed for modelling selection by 28 spotted owls (Strix occidentalis) as well as a generalized nested logit model using random utility maximization and a random RSPF. Numerical optimization methods and the SAS system were employed to estimate the nested structural parameters.

One major lesson derived from the implementation of the Endangered Species Act (ESA) over the past 30 years is that direct regulation is not the only nor the optimal way to protect endangered species on working lands because of an undue burden imposed on private landowners. The role of a voluntary conservation program is to rearrange incentives so that society bears the cost rather than the landowner. Employing a survey research methodology, I used theories of reasoned action and random choice to explore landowners? stated preferences for conservation programs. I found landowners? stated interest in compensation programs to be moderate at best. For those willing to consider programs involving endangered species, associating land management requirements for species conservation with direct benefits to the landowner is important, but perhaps not as important as ensuring that the program provides adequate financial incentives, consideration of the term of the program, and a level of certainty regarding the landowner?s future obligations under the ESA. Landowners are not a homogenous group. I identified two classes of landowners according to preferences for program structure. One group was highly sensitive to program structure, aside from financial incentives, while the other was likely to participate if adequately compensated with financial and technical assistance. These differences related to opinions on endangered species protection and dependence on their land for income. Voluntary incentive programs increasingly are a popular tool to maintain and enhance conservation; however, these programs are only successful insofar as landowners choose to enroll. This research demonstrates that improving recovery efforts on private lands requires program administrators to have a more complete understanding of landowners? views on endangered species and conservation programs in general, as well as their motivations for owning and operating their land. By doing so, programs with broader appeal and greater efficacy can be designed and implemented.

Diese Arbeit stellt grundlegend zwei Modellentwicklungen der Verkehrsangebots- und Verkehrsnachfragemodellierung vor. Die erste Entwicklung bezieht sich auf die simultane Ziel- und Verkehrsmittelwahl in Abhängigkeit von Strukturgrößen und/oder Lagegunst. Es werden neue Randsummenbedingungen beschrieben und vorhandene neu definiert. Der neue Modellansatz erlaubt eine Bestimmung minimaler und maximaler Verkehrsaufkommen und stellt eine Erweiterung der theoretischen Grundlagen als auch der praktischen Anwendbarkeit dar. So können alle derzeit bekannten Randsummenbedingungen durch einen Algorithmus (auch innerhalb einer Quelle-Ziel-Gruppe) berechnet werden. Der zweite Ansatz ist ein Werkzeug, welches in Abhängigkeit des vorhandenen Verkehrsangebotes verkehrsplanerisch wünschenswerte quantitative Flächen- bzw. Gebietsnutzungen abschätzt. Aufbauend auf der Verkehrsangebots- und Verkehrsnachfragemodellierung werden Infrastrukturgrößen durch eine aufzustellende Zielfunktion (z. B. minimale Verkehrsarbeit), unter Beachtung vorhandener Freiheitsgrade der Flächennutzung je Verkehrsbezirk, optimiert. Diese Freiheitsgrade werden als minimale und maximale Strukturgrößengrenzen durch die Raum- und Stadtplanung definiert, womit sie den vielfältigen Einflussgrößen dieser Planungen unterliegen und dadurch städtebaulich verträglich sind. Der Modellansatz bildet die für die Infrastrukturplanung wichtigen Wechselwirkungen des durch den Stadt- und Verkehrsplaner angestrebten Systemoptimums (Infrastrukturgrößenverteilung eines Gebietes) mit dem durch den einzelnen Verkehrsteilnehmer angestrebten Nutzenoptimum (Verkehrsnachfrage) ab. / This work basically introduces two model developments of traffic supply and traffic demand modeling. The first development refers to the simultaneous destination and mode choice into dependence of structure sizes and/or accessibility. New constraints are described and available constraints were defined newly. The new model enables the determination of minimal and maximum volumes of traffic (constraints). The new explanatory model is an expansion of the theoretical bases and the practical applicability. So all currently known constraints can be calculated by one algorithm (also within an origin destination group). The second approach is a tool which describes desirable quantitative traffic planningly land uses against the available traffic supply. It uses an algorithm that keeps minimal and maximum structure size limits while it determining e.g. minimal traffic work. Within the algorithm the complete traffic demand will be calculated. The complete model shows the important interactions of the infrastructure planning by the town and transport planer (a striven system optimum) with the traffic demand by the single road user (a striven user equilibrium).

Em ecologia, o comportamento dos animais é freqüentemente estudado para entender melhor suas preferências por diferentes tipos de alimento e habitat. O presente trabalho esta relacionado a este tópico, dividindo-se em três capítulos. O primeiro capitulo refere-se à estimação da função da probabilidade da seleção de recurso (RSPF) comparado com um modelo de escolha discreta (DCM) com uma escolha, usando as estatísticas qui-quadrado para obter as estimativas. As melhores estimativas foram obtidas pelo método DCM com uma escolha. No entanto, os animais não fazem a sua seleção baseados apenas em uma escolha. Com RSPF, as estimativas de máxima verossimilhança, usadas pela regressão logística ainda não atingiram os objetivos, já que os animais têm mais de uma escolha. R e o software Minitab e a linguagem de programação Fortran foram usados para obter os resultados deste capítulo. No segundo capítulo discutimos mais a verossimilhança do primeiro capítulo. Uma nova verossimilhança para a RSPF é apresentada, a qual considera as unidades usadas e não usadas, e métodos de bootstrapping paramétrico e não paramétrico são usados para estudar o viés e a variância dos estimadores dos parâmetros, usando o programa FORTRAN para obter os resultados. No terceiro capítulo, a nova verossimilhança apresentada no capítulo 2 é usada com um modelo de escolha discreta, para resolver parte do problema apresentado no primeiro capítulo. A estrutura de encaixe é proposta para modelar a seleção de habitat de 28 corujas manchadas (Strix occidentalis), assim como a uma generalização do modelo logit encaixado, usando a maximização da utilidade aleatória e a RSPF aleatória. Métodos de otimização numérica, e o sistema computacional SAS, são usados para estimar os parâmetros de estrutura de encaixe. / In ecology, the behavior of animals is often studied to better understand their preferences for different types of habitat and food. The present work is concerned with this topic. It is divided into three chapters. The first concerns the estimation of a resource selection probability function (RSPF) compared with a discrete choice model (DCM) using chi-squared to obtain estimates. The best estimates were obtained by the DCM method. Nevertheless, animals were not selected based on choice alone. With RSPF, the maximum likelihood estimates used with the logistic regression still did not reach the objectives, since the animals have more than one choice. R and Minitab software and the FORTRAN programming language were used for the computations in this chapter. The second chapter discusses further the likelihood presented in the first chapter. A new likelihood for a RSPF is presented, which takes into account the units used and not used, and parametric and non-parametric bootstrapping are employed to study the bias and variance of parameter estimators, using a FORTRAN program for the calculations. In the third chapter, the new likelihood presented in chapter 2, with a discrete choice model is used to resolve a part of the problem presented in the first chapter. A nested structure is proposed for modelling selection by 28 spotted owls (Strix occidentalis) as well as a generalized nested logit model using random utility maximization and a random RSPF. Numerical optimization methods and the SAS system were employed to estimate the nested structural parameters.

Cette thèse s'intéresse à la réconciliation entre le défi mondial du changement climatique et les solutions locales et sectorielles qu'il convient de bien articuler pour contribuer, efficacement, équitablement et de la manière la plus acceptable, à la réduction des émissions de CO2. Plus précisément, nous étudions les conditions pour une mise en place réussie de la politique climatique à l'échelle de la mobilité urbaine des personnes. / This PhD thesis deals with the reconciliation of the global challenge that is climate change and the local and sectoral solutions that need to be accurately designed to remedy to it the most efficiently, equitably and acceptably possible. More specifically, we investigate the conditions for a successful implementation of climate policy at the scale of the urban mobility of passengers.

Diese Arbeit stellt grundlegend zwei Modellentwicklungen der Verkehrsangebots- und Verkehrsnachfragemodellierung vor. Die erste Entwicklung bezieht sich auf die simultane Ziel- und Verkehrsmittelwahl in Abhängigkeit von Strukturgrößen und/oder Lagegunst. Es werden neue Randsummenbedingungen beschrieben und vorhandene neu definiert. Der neue Modellansatz erlaubt eine Bestimmung minimaler und maximaler Verkehrsaufkommen und stellt eine Erweiterung der theoretischen Grundlagen als auch der praktischen Anwendbarkeit dar. So können alle derzeit bekannten Randsummenbedingungen durch einen Algorithmus (auch innerhalb einer Quelle-Ziel-Gruppe) berechnet werden. Der zweite Ansatz ist ein Werkzeug, welches in Abhängigkeit des vorhandenen Verkehrsangebotes verkehrsplanerisch wünschenswerte quantitative Flächen- bzw. Gebietsnutzungen abschätzt. Aufbauend auf der Verkehrsangebots- und Verkehrsnachfragemodellierung werden Infrastrukturgrößen durch eine aufzustellende Zielfunktion (z. B. minimale Verkehrsarbeit), unter Beachtung vorhandener Freiheitsgrade der Flächennutzung je Verkehrsbezirk, optimiert. Diese Freiheitsgrade werden als minimale und maximale Strukturgrößengrenzen durch die Raum- und Stadtplanung definiert, womit sie den vielfältigen Einflussgrößen dieser Planungen unterliegen und dadurch städtebaulich verträglich sind. Der Modellansatz bildet die für die Infrastrukturplanung wichtigen Wechselwirkungen des durch den Stadt- und Verkehrsplaner angestrebten Systemoptimums (Infrastrukturgrößenverteilung eines Gebietes) mit dem durch den einzelnen Verkehrsteilnehmer angestrebten Nutzenoptimum (Verkehrsnachfrage) ab. / This work basically introduces two model developments of traffic supply and traffic demand modeling. The first development refers to the simultaneous destination and mode choice into dependence of structure sizes and/or accessibility. New constraints are described and available constraints were defined newly. The new model enables the determination of minimal and maximum volumes of traffic (constraints). The new explanatory model is an expansion of the theoretical bases and the practical applicability. So all currently known constraints can be calculated by one algorithm (also within an origin destination group). The second approach is a tool which describes desirable quantitative traffic planningly land uses against the available traffic supply. It uses an algorithm that keeps minimal and maximum structure size limits while it determining e.g. minimal traffic work. Within the algorithm the complete traffic demand will be calculated. The complete model shows the important interactions of the infrastructure planning by the town and transport planer (a striven system optimum) with the traffic demand by the single road user (a striven user equilibrium).

El mundo de las telecomunicaciones está cambiando de un escenario donde únicamente las personas estaban conectadas a un modelo donde prácticamente todos los dispositivos y sensores se encuentran conectados, también conocido como Internet de las cosas (IoT), donde miles de millones de dispositivos se conectarán a Internet a través de conexiones móviles y redes fijas. En este contexto, hay muchos retos que superar, desde el desarrollo de nuevos estándares de comunicación al estudio de la viabilidad económica de los posibles escenarios futuros. En esta tesis nos hemos centrado en el estudio de la viabilidad económica de diferentes escenarios mediante el uso de conceptos de microeconomía, teoría de juegos, optimización no lineal, economía de redes y redes inalámbricas. La tesis analiza la transición desde redes centradas en el servicio de tráfico HTC a redes centradas en tráfico MTC desde un punto de vista económico. El primer escenario ha sido diseñado para centrarse en las primeras etapas de la transición, en la que ambos tipos de tráfico son servidos bajo la misma infraestructura de red. En el segundo escenario analizamos la siguiente etapa, en la que el servicio a los usuarios MTC se realiza mediante una infraestructura dedicada. Finalmente, el tercer escenario analiza la provisión de servicios basados en MTC a usuarios finales, mediante la infraestructura analizada en el escenario anterior. Gracias al análisis de todos los escenarios, hemos observado que la transición de redes centradas en usuarios HTC a redes MTC es posible y que la provisión de servicios en tales escenarios es viable. Además, hemos observado que el comportamiento de los usuarios es esencial para determinar la viabilidad de los diferentes modelos de negocio, y por tanto, es necesario estudiar el comportamiento y las preferencias de los usuarios en profundidad en estudios futuros. Específicamente, los factores más relevantes son la sensibilidad de los usuarios al retardo en los datos recopilados por los sensores y la cantidad de los mismos. También hemos observado que la diferenciación del tráfico en categorías mejora el uso de las redes y permite crear nuevos servicios empleando datos que, de otro modo, no se aprovecharían, lo cual nos permite mejorar la monetización de la infraestructura. También hemos demostrado que la provisión de capacidad es un mecanismo válido, alternativo a la fijación de precios, para la optimización de los beneficios de los proveedores de servicio. Finalmente, se ha demostrado que es posible crear roles específicos para ofrecer servicios IoT en el mercado de las telecomunicaciones, específicamente, los IoT-SPs, que proporcionan servicios basados en sensores inalámbricos utilizando infraestructuras de acceso de terceros y sus propias redes de sensores. En resumen, en esta tesis hemos intentado demostrar la viabilidad económica de modelos de negocio basados en redes futuras IoT, así como la aparición de nuevas oportunidades y roles de negocio, lo cual nos permite justificar económicamente el desarrollo y la implementación de las tecnologías necesarias para ofrecer servicios de acceso inalámbrico masivo a dispositivos MTC. / The communications world is moving from a standalone devices scenario to a all-connected scenario known as Internet of Things (IoT), where billions of devices will be connected to the Internet through mobile and fixed networks. In this context, there are several challenges to face, from the development of new standards to the study of the economical viability of the different future scenarios. In this dissertation we have focused on the study of the economic viability of different scenarios using concepts of microeconomics, game theory, non-linear optimization, network economics and wireless networks. The dissertation analyzes the transition from a Human Type Communications (HTC) to a Machine Type Communications (MTC) centered network from an economic point of view. The first scenario is designed to focus on the first stages of the transition, where HTC and MTC traffic are served on a common network infrastructure. The second scenario analyzes the provision of connectivity service to MTC users using a dedicated network infrastructure, while the third stage is centered in the analysis of the provision of services based on the MTC data over the infrastructure studied in the previous scenario. Thanks to the analysis of all the scenarios we have observed that the transition from HTC users-centered networks to MTC networks is possible and that the provision of services in such scenarios is viable. In addition, we have observed that the behavior of the users is essential in order to determine the viability of a business model, and therefore, it is needed to study their behavior and preferences in depth in future studios. Specifically, the most relevant factors are the sensitivity of the users to the delay and to the amount of data gathered by the sensors. We also have observed that the differentiation of the traffic in categories improves the usage of the networks and allows to create new services thanks to the data that otherwise would not be used, improving the monetization of the infrastructure and the data. In addition, we have shown that the capacity provision is a valid mechanism for providers' profit optimization, as an alternative to the pricing mechanisms. Finally, it has been demonstrated that it is possible to create dedicated roles to offer IoT services in the telecommunications market, specifically, the IoT-SPs, which provide wireless-sensor-based services to the final users using a third party infrastructure. Summarizing, this dissertation tries to demonstrate the economic viability of the future IoT networks business models as well as the emergence of new business opportunities and roles in order to justify economically the development and implementation of the new technologies required to offer massive wireless access to machine devices. / El món de les telecomunicacions està canviant d'un escenari on únicament les persones estaven connectades a un model on pràcticament tots els dispositius i sensors es troben connectats, també conegut com a Internet de les Coses (IoT) , on milers de milions de dispositius es connectaran a Internet a través de connexions mòbils i xarxes fixes. En aquest context, hi ha molts reptes que superar, des del desenrotllament de nous estàndards de comunicació a l'estudi de la viabilitat econòmica dels possibles escenaris futurs. En aquesta tesi ens hem centrat en l'estudi de la viabilitat econòmica de diferents escenaris per mitjà de l'ús de conceptes de microeconomia, teoria de jocs, optimització no lineal, economia de xarxes i xarxes inalàmbriques. La tesi analitza la transició des de xarxes centrades en el servici de tràfic HTC a xarxes centrades en tràfic MTC des d'un punt de vista econòmic. El primer escenari ha sigut dissenyat per a centrar-se en les primeres etapes de la transició, en la que ambdós tipus de tràfic són servits davall la mateixa infraestructura de xarxa. En el segon escenari analitzem la següent etapa, en la que el servici als usuaris MTC es realitza per mitjà d'una infraestructura dedicada. Finalment, el tercer escenari analitza la provisió de servicis basats en MTC a usuaris finals, per mitjà de la infraestructura analitzada en l'escenari anterior. Als paràgrafs següents es descriu amb més detall cada escenari. Gràcies a l'anàlisi de tots els escenaris, hem observat que la transició de xarxes centrades en usuaris HTC a xarxes MTC és possible i que la provisió de servicis en tals escenaris és viable. A més a més, hem observat que el comportament dels usuaris és essencial per a determinar la viabilitat dels diferents models de negoci, i per tant, és necessari estudiar el comportament i les preferències dels usuaris en profunditat en estudis futurs. Específicament, els factors més rellevants són la sensibilitat dels usuaris al retard en les dades recopilats pels sensors i la quantitat dels mateixos. També hem observat que la diferenciació del tràfic en categories millora l'ús de les xarxes i permet crear nous servicis emprant dades que, d'una altra manera, no s'aprofitarien, la qual cosa ens permet millorar la monetització de la infraestructura. També hem demostrat que la provisió de capacitat és un mecanisme vàlid, alternatiu a la fixació de preus, per a l'optimització dels beneficis dels proveïdors de servici. Finalment, s'ha demostrat que és possible crear rols específics per a oferir servicis IoT en el mercat de les telecomunicacions, específicament, els IoT-SPs, que proporcionen servicis basats en sensors inalàmbrics utilitzant infraestructures d'accés de tercers i les seues pròpies xarxes de sensors. En resum, en aquesta tesi hem intentat demostrar la viabilitat econòmica de models de negoci basats en xarxes futures IoT, així com l'aparició de noves oportunitats i rols de negoci, la qual cosa ens permet justificar econòmicament el desenrotllament i la implementació de les tecnologies necessàries per a oferir servicis d'accés inalàmbric massiu a dispositius MTC. / Sanchis Cano, Á. (2018). Economic analysis of wireless sensor-based services in the framework of the Internet of Things. A game-theoretical approach [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/102642

In der akademischen Fachliteratur existieren kaum Forschungsergebnisse zu One-to-One-Marketing, die auf Anwendungen im Einzelhandel ausgerichtet sind. Zu den Hauptgründen zählen, dass Ansätze nicht auf die Größe typischer Einzelhandelsanwendungen skalieren und dass die Datenverfügbarkeit auf Händler und Marketing-Systemanbieter beschränkt ist. Die vorliegende Dissertation entwickelt neue deskriptive, prädiktive und präskriptive Modelle für automatisiertes Target Marketing, die auf Representation Learning und Deep Learning basieren, und untersucht deren Wirksamkeit in Praxisanwendungen. Im ersten Schritt zeigt die Arbeit, dass Representation Learning in der Lage ist, skalierbar Marktstrukturen zu analysieren. Der vorgeschlagene Ansatz zur Visualisierung von Marktstrukturen ist vollständig automatisiert und existierenden Methoden überlegen. Die Arbeit entwickelt anschließend ein skalierbares, nichtparametrisches Modell, das Produktwahl auf Konsumentenebene für alle Produkte im Sortiment großer Einzelhändler vorhersagt. Das Deep Neural Network übertrifft die Vorhersagekraft existierender Benchmarks und auf Basis des Modells abgeleitete Coupons erzielen signifikant höhere Umsatzsteigerungen. Die Dissertation untersucht abschließend eine Coupon-Engine, die auf den entwickelten Modellen basiert. Der Vergleich personalisierter Werbeaktionen mit Massenmarketing belegt, dass One-to-One Marketing Einlösungsraten, Umsätze und Gewinne steigern kann. Eine Analyse der Kundenreaktionen auf personalisierte Coupons im Rahmen eines Kundenbindungsprogrammes zeigt, dass personalisiertes Marketing Systemnutzung erhöht. Dies illustriert, wie Target Marketing und Kundenbindungsprogramme effizient kombiniert werden können. Die vorliegende Dissertation ist somit sowohl für Forscher als auch für Praktiker relevant. Neben leistungsfähigeren Modellansätzen bietet diese Arbeit relevante Implikationen für effizientes Promotion-Management und One-to-One-Marketing im Einzelhandel. / Research on one-to-one marketing with a focus on retailing is scarce in academic literature. The two main reasons are that the target marketing approaches proposed by researchers do not scale to the size of typical retail applications and that data regarding one-to-one marketing remain locked within retailers and marketing solution providers. This dissertation develops new descriptive, predictive, and prescriptive marketing models for automated target marketing that are based on representation learning and deep learning and studies the models’ impact in real-life applications. First, this thesis shows that representation learning is capable of analyzing market structures at scale. The proposed approach to visualizing market structures is fully automated and superior to existing mapping methods that are based on the same input data. The thesis then proposes a scalable, nonparametric model that predicts product choice for the entire assortment of a large retailer. The deep neural network outperforms benchmark methods for predicting customer purchases. Coupon policies based on the proposed model lead to substantially higher revenue lifts than policies based on the benchmark models. The remainder of the thesis studies a real-time offer engine that is based on the proposed models. The comparison of personalized promotions to non-targeted promotions shows that one-to-one marketing increases redemption rates, revenues, and profits. A study of customer responses to personalized price promotions within the retailer’s loyalty program reveals that personalized marketing also increases loyalty program usage. This illustrates how targeted price promotions can be integrated smoothly into loyalty programs. In summary, this thesis is highly relevant for both researchers and practitioners. The new deep learning models facilitate more scalable and efficient one-to-one marketing. In addition, this research offers pertinent implications for promotion management and one-to-one marketing.

Ce mémoire de thèse porte sur la statistique inférentielle des données spatiales et/ou fonctionnelles. En effet, nous nous sommes intéressés à l’estimation de paramètres inconnus de certains modèles à partir d’échantillons obtenus par un processus d’échantillonnage aléatoire ou non (stratifié), composés de variables indépendantes ou spatialement dépendantes.La spécificité des méthodes proposées réside dans le fait qu’elles tiennent compte de la nature de l’échantillon étudié (échantillon stratifié ou composé de données spatiales dépendantes).Tout d’abord, nous étudions des données à valeurs dans un espace de dimension infinie ou dites ”données fonctionnelles”. Dans un premier temps, nous étudions les modèles de choix binaires fonctionnels dans un contexte d’échantillonnage par stratification endogène (échantillonnage Cas-Témoin ou échantillonnage basé sur le choix). La spécificité de cette étude réside sur le fait que la méthode proposée prend en considération le schéma d’échantillonnage. Nous décrivons une fonction de vraisemblance conditionnelle sous l’échantillonnage considérée et une stratégie de réduction de dimension afin d’introduire une estimation du modèle par vraisemblance conditionnelle. Nous étudions les propriétés asymptotiques des estimateurs proposées ainsi que leurs applications à des données simulées et réelles. Nous nous sommes ensuite intéressés à un modèle linéaire fonctionnel spatial auto-régressif. La particularité du modèle réside dans la nature fonctionnelle de la variable explicative et la structure de la dépendance spatiale des variables de l’échantillon considéré. La procédure d’estimation que nous proposons consiste à réduire la dimension infinie de la variable explicative fonctionnelle et à maximiser une quasi-vraisemblance associée au modèle. Nous établissons la consistance, la normalité asymptotique et les performances numériques des estimateurs proposés.Dans la deuxième partie du mémoire, nous abordons des problèmes de régression et prédiction de variables dépendantes à valeurs réelles. Nous commençons par généraliser la méthode de k-plus proches voisins (k-nearest neighbors; k-NN) afin de prédire un processus spatial en des sites non-observés, en présence de co-variables spatiaux. La spécificité du prédicteur proposé est qu’il tient compte d’une hétérogénéité au niveau de la co-variable utilisée. Nous établissons la convergence presque complète avec vitesse du prédicteur et donnons des résultats numériques à l’aide de données simulées et environnementales.Nous généralisons ensuite le modèle probit partiellement linéaire pour données indépendantes à des données spatiales. Nous utilisons un processus spatial linéaire pour modéliser les perturbations du processus considéré, permettant ainsi plus de flexibilité et d’englober plusieurs types de dépendances spatiales. Nous proposons une approche d’estimation semi paramétrique basée sur une vraisemblance pondérée et la méthode des moments généralisées et en étudions les propriétés asymptotiques et performances numériques. Une étude sur la détection des facteurs de risque de cancer VADS (voies aéro-digestives supérieures)dans la région Nord de France à l’aide de modèles spatiaux à choix binaire termine notre contribution. / This thesis is about statistical inference for spatial and/or functional data. Indeed, weare interested in estimation of unknown parameters of some models from random or nonrandom(stratified) samples composed of independent or spatially dependent variables.The specificity of the proposed methods lies in the fact that they take into considerationthe considered sample nature (stratified or spatial sample).We begin by studying data valued in a space of infinite dimension or so-called ”functionaldata”. First, we study a functional binary choice model explored in a case-controlor choice-based sample design context. The specificity of this study is that the proposedmethod takes into account the sampling scheme. We describe a conditional likelihoodfunction under the sampling distribution and a reduction of dimension strategy to definea feasible conditional maximum likelihood estimator of the model. Asymptotic propertiesof the proposed estimates as well as their application to simulated and real data are given.Secondly, we explore a functional linear autoregressive spatial model whose particularityis on the functional nature of the explanatory variable and the structure of the spatialdependence. The estimation procedure consists of reducing the infinite dimension of thefunctional variable and maximizing a quasi-likelihood function. We establish the consistencyand asymptotic normality of the estimator. The usefulness of the methodology isillustrated via simulations and an application to some real data.In the second part of the thesis, we address some estimation and prediction problemsof real random spatial variables. We start by generalizing the k-nearest neighbors method,namely k-NN, to predict a spatial process at non-observed locations using some covariates.The specificity of the proposed k-NN predictor lies in the fact that it is flexible and allowsa number of heterogeneity in the covariate. We establish the almost complete convergencewith rates of the spatial predictor whose performance is ensured by an application oversimulated and environmental data. In addition, we generalize the partially linear probitmodel of independent data to the spatial case. We use a linear process for disturbancesallowing various spatial dependencies and propose a semiparametric estimation approachbased on weighted likelihood and generalized method of moments methods. We establishthe consistency and asymptotic distribution of the proposed estimators and investigate thefinite sample performance of the estimators on simulated data. We end by an applicationof spatial binary choice models to identify UADT (Upper aerodigestive tract) cancer riskfactors in the north region of France which displays the highest rates of such cancerincidence and mortality of the country.