Neste trabalho consideramos um processo de Markov a tempo contínuo com espaço de estados finito em um meio aleatório, a saber, a dinâmica de Metropolis para o Modelo de Energia Aleatória Generalizado (GREM) com um número de níveis finito e discutimos o comportamento do seu tempo de chegada ao equilíbrio, o qual é dado pelo inverso da lacuna espectral de sua matriz de probabilidades de transição. No principal resultado desta tese provamos que o quociente entre o volume do sistema e o logaritmo do inverso da lacuna é quase sempre limitado, por cima, por uma função da temperatura, que também é a que descreve a energia livre do GREM sob o regime de temperaturas baixas. Como um estudo adicional, também é discutido um correspondente limitante inferior em um caso particular do GREM com 2 níveis. / In this work we consider a finite state continuous-time Markov process in a random environment, namely, the Metropolis dynamics for the Generalized Random Energy Model (GREM) with a finite number of levels, and we discuss the behavior of its reaching time to equilibrium which is given by inverse of the spectral gap of its transition probability matrix. On the main result of this thesis, we prove the division between the system volume and the logarithm of the inverse of the gap is almost surely upper bounded by a function of the temperature that it is also the function that describe the free energy of the GREM at low temperature. As an additional study, it is also discuss the corresponding limiting lower in a particular case of the 2-level GREM.

A análise fatorial é uma importante ferramenta estatística que tem amplas aplicações práticas e explica a correlação entre um grande número de variáveis observáveis em termos de um pequeno número de variáveis não observáveis, conhecidas como variáveis latentes. A proposta deste trabalho é fazer a análise Bayesiana, que incorpora à análise o conhecimento que se tenha sobre os parâmetros antes da coleta dos dados, do modelo fatorial dinâmico na classe de modelos elípticos multivariados, assumindo que a um vetor de q séries temporais pode-se ajustar um modelo fatorial com k < q fatores mais um ruído branco, e que a parte latente segue um modelo vetorial auto-regressivo. A classe de modelos elípticos citada acima é rica em distribuições simétricas com caudas mais pesadas que as da distribuição normal, característica importante na análise de séries financeiras. Essa classe inclui as distribuições t de Student, exponencial potência, normal contaminada, entre outras. A inferência sobre os parâmetros foi feita utilizando métodos de Monte Carlo via Cadeias de Markov, com os algoritmos Metropolis-Hastings e Griddy-Gibbs, através da obtenção das distribuições a posteriori dos parâmetros e dos fatores. A determinação da convergência do processo foi feita por técnicas gráficas e pelos métodos de Geweke (1992), de Heidelberger e Welch (1983) e Half-Width. O método foi ilustrado usando dados reais e simulados. / The factor analysis is an important statistical tool that has wide practical applications and it explains the correlation among a large number of observable variables in terms of a small number of unobservable variables, known as latent variables. The proposal of this work is the Bayesian analysis, which incorporates the information we have concerning the parameters before collecting data into the analysis of a dynamical factor model in the class of multivariate elliptical models, where the factors follow a multivariate autoregressive model, assuming that a vector of q time series can be adjusted with k < q factors and a white noise. The class of elliptical models is rich in symmetrical distributions with heavier tails than the normal distribution, which is an important characteristic in financial series analysis. This class includes t-Student, power exponential, contaminated normal and other distributions. The parameters inference was made through Monte Carlo Markov Chain methods, with Metropolis-Hastings and Griddy-Gibbs algorithms, by obtaining the parameters and factors posteriori distributions. The convergence process was made through graphical technics and by Geweke (1992) and by Heidelberger and Welch (1983) and Half- Width methods. The method was illustrated using simulated and real data.

Selon la théorie de Cottrell et Bilby, les dislocations à travers leur champ de contrainte interagissent avec les atomes de soluté qui s’agrègent au cœur et autour des dislocations (atmosphère de Cottrell). Ces atmosphères « bloquent » les dislocations et fragilisent le matériau. Dans cette thèse, les techniques de simulations à l’échelle atomique telles que la Dynamique Moléculaire, les simulations Monte Carlo Cinétique, Monte Carlo Métropolis ont été développées qui permettent de prendre en compte les interactions entre plusieurs centaines d’atomes de carbone et la dislocation, pour étudier la cinétique de formation ainsi que la structure d’une atmosphère de Cottrell. Par ailleurs, la technique de simulation est appliquée à deux autres problématiques: premièrement, il est connu que les atomes de C dans la ferrite se mettent en ordre (mise en ordre de Zener). La stabilité de cette phase est étudiée en fonction de la température et la concentration de C. Deuxièmement, la ségrégation des atomes de soluté dans les nano-cristaux de Ni ainsi que la stabilité des nano-cristaux avec les atomes de soluté dans les joints de grain à haute température est étudiée. / The objective of the thesis was to understand the microscopic features at the origin of ageing in metals. The originality of this contribution was the com- bination of three complementary computational techniques : (1) Metropolis Monte Carlo (MMC), (2) Atomic Kinetic Monte Carlo (AKMC), and, (3) Molecular Dynamics (MD). It consisted of four main sections : Firstly the ordering occurring in bulk alpha-iron via MMC and MD was studied. Various carbon contents and temperatures were investigated in order to obtain a “phase diagram”. Secondly, the generation of systems containing a dislocation interacting with many carbon atoms, namely a Cottrell Atmosphere, with MMC technique was described. The equilibrium structure of the atmosphere and the stress field around the atmospheres proves that the stress field around the dislocation was affected but not cancelled out by the atmosphere. Thirdly, the kinetics of the carbon migration and Cottrell atmosphere evolution were investigated via AKMC. The activation energies for carbon atom migration were calculated from the local stress field and the arrangement of the neigh- bouring carbon atoms. Lastly, an application of the combined use of MMC and MD to describe grain boundary segregation of solute atoms in fcc nickel was presented. The grain growth was inhibited due to the solute atoms in the grain boundary.

Submitted by (ana.araujo@ufrpe.br) on 2016-08-01T17:35:24Z No. of bitstreams: 1 Kleber Napoleao Nunes de Oliveira Barros.pdf: 2964667 bytes, checksum: a3c757cb7ed16fc9c38b7834b6e0fa29 (MD5) / Made available in DSpace on 2016-08-01T17:35:24Z (GMT). No. of bitstreams: 1 Kleber Napoleao Nunes de Oliveira Barros.pdf: 2964667 bytes, checksum: a3c757cb7ed16fc9c38b7834b6e0fa29 (MD5) Previous issue date: 2010-02-22 / It is presented in this work the growth model nonlinear Chapman-Richards with distribution of errors following the new class of symmetric models processed and Bayesian inference for the parameters. The objective was to apply this structure, via Metropolis-Hastings algorithm, in order to select the equation that best predicted heights of clones of Eucalyptus urophilla experiment established at the Agronomic Institute of Pernambuco (IPA) in the city of Araripina . The Gypsum Pole of Araripe is an industrial zone, located on the upper interior of Pernambuco, which consumes large amount of wood from native vegetation (caatinga) for calcination of gypsum. In this scenario, there is great need for a solution, economically and environmentally feasible that allows minimizing the pressure on native vegetation. The generus Eucalyptus presents itself as an alternative for rapid development and versatility. The height has proven to be an important factor in prognosis of productivity and selection of clones best adapted. One of the main growth curves, is the Chapman-Richards model with normal distribution for errors. However, some alternatives have been proposed in order to reduce the influence of atypical observations generated by this model. The data were taken from a plantation, with 72 months. Were performed inferences and diagnostics for processed and unprocessed model with many distributions symmetric. After selecting the best equation, was shown some convergence of graphics and other parameters that show the fit to the data model transformed symmetric Student’s t with 5 degrees of freedom in the parameters using Bayesian inference. / É abordado neste trabalho o modelo de crescimento não linear de Chapman-Richards com distribuição dos erros seguindo a nova classe de modelos simétricos transformados e inferência Bayesiana para os parâmetros. O objetivo foi aplicar essa estrutura, via algoritmo de Metropolis-Hastings, afim de selecionar a equação que melhor estimasse as alturas de clones de Eucalyptus urophilla provenientes de experimento implantado no Instituto Agronômico de Pernambuco (IPA), na cidade de Araripina. O Polo Gesseiro do Araripe é uma zona industrial, situada no alto sertão pernambucano, que consume grande quantidade de lenha proveniente da vegetação nativa (caatinga) para calcinação da gipsita. Nesse cenário, há grande necessidade de uma solução, econômica e ambientalmente, viável que possibilite uma minimização da pressão sobre a flora nativa. O gênero Eucalyptus se apresenta como alternativa, pelo seu rápido desenvolvimento e versatilidade. A altura tem se revelado fator importante na prognose de produtividade e seleção de clones melhores adaptados. Uma das principais curvas de crescimento, é o modelo de Chapman- Richards com distribuição normal para os erros. No entanto, algumas alternativas tem sido propostas afim de reduzir a influência de observações atípicas geradas por este modelo. Os dados foram retirados de uma plantação, com 72 meses. Foram realizadas as inferências e diagnósticos para modelo transformado e não transformado com diversas distribuições simétricas. Após a seleção da melhor equação, foram mostrados alguns gráficos da convergência dos parâmetros e outros que comprovam o ajuste aos dados do modelo simétrico transformado t de Student com 5 graus de liberdade utilizando inferência Bayesiana nos parâmetros.

Neste trabalho consideramos um processo de Markov a tempo contínuo com espaço de estados finito em um meio aleatório, a saber, a dinâmica de Metropolis para o Modelo de Energia Aleatória Generalizado (GREM) com um número de níveis finito e discutimos o comportamento do seu tempo de chegada ao equilíbrio, o qual é dado pelo inverso da lacuna espectral de sua matriz de probabilidades de transição. No principal resultado desta tese provamos que o quociente entre o volume do sistema e o logaritmo do inverso da lacuna é quase sempre limitado, por cima, por uma função da temperatura, que também é a que descreve a energia livre do GREM sob o regime de temperaturas baixas. Como um estudo adicional, também é discutido um correspondente limitante inferior em um caso particular do GREM com 2 níveis. / In this work we consider a finite state continuous-time Markov process in a random environment, namely, the Metropolis dynamics for the Generalized Random Energy Model (GREM) with a finite number of levels, and we discuss the behavior of its reaching time to equilibrium which is given by inverse of the spectral gap of its transition probability matrix. On the main result of this thesis, we prove the division between the system volume and the logarithm of the inverse of the gap is almost surely upper bounded by a function of the temperature that it is also the function that describe the free energy of the GREM at low temperature. As an additional study, it is also discuss the corresponding limiting lower in a particular case of the 2-level GREM.

Submitted by Renata Lopes (renatasil82@gmail.com) on 2017-06-08T13:54:44Z No. of bitstreams: 1 evertonluizmartinsdapaixao.pdf: 7260792 bytes, checksum: 8a1a1accd3cfb65d925f1429e761f688 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2017-06-26T19:03:05Z (GMT) No. of bitstreams: 1 evertonluizmartinsdapaixao.pdf: 7260792 bytes, checksum: 8a1a1accd3cfb65d925f1429e761f688 (MD5) / Made available in DSpace on 2017-06-26T19:03:05Z (GMT). No. of bitstreams: 1 evertonluizmartinsdapaixao.pdf: 7260792 bytes, checksum: 8a1a1accd3cfb65d925f1429e761f688 (MD5) Previous issue date: 2013-04-19 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Neste trabalho usamos o método de Monte Carlo Metropolis aplicado em sistemas magnéticos para estudar nanoestruturas como nanodiscos e nanofios de Permalloy. Dividimos em duas partes. Primeiramente, estudou-se o comportamento do núcleo do vórtice rodeado por anéis de impurezas em nanodiscos de permalloy. Variamos o raio e a espessura dos anéis e medimos o limite do campo aplicado para que o núcleo do vórtice passe através destes anéis. Em segundo lugar, temos estudado os estados fundamentais (de menor energia) para nanofios para uma pequena região do espaço de fase. Podemos identificar as configurações de rotação associadas a estes estados. / In this work we have used Monte Carlo Metropolis method applied in magnetic systems to study nanostructures like permalloy nanodisks and nanowires. We divided it in two parts. First, we have studied the behavior of the vortex core surrounded by rings of the impurities in permalloy nanodisks. We have varied the radius and the thickness of the rings and we measure the limit of the applied field for that the vortex core passes through the ring. Second, we have studied the ground states (lowest-energy state) for nanowires to a small region of the phase space. We can identify the spin configurations associated to the these states.

Nous étudions la régression bayésienne sous contraintes de régularité et de forme. Pour cela,on considère une base de B-spline pour obtenir une courbe lisse et nous démontrons que la forme d'une spline engendrée par une base de B-spline est contrôlée par un ensemble de points de contrôle qui ne sont pas situés sur la courbe de la spline. On propose différents types de contraintes de forme (monotonie, unimodalité, convexité, etc). Ces contraintes sont prises en compte grâce à la loi a priori. L'inférence bayésienne a permis de dériver la distribution posteriori sous forme explicite à une constante près. En utilisant un algorithme hybride de type Metropolis-Hastings avec une étape de Gibbs, on propose des simulations suivant la distribution a posteriori tronquée. Nous estimons la fonction de régression par le mode a posteriori. Un algorithme de type recuit simulé a permis de calculer le mode a posteriori. La convergence des algorithmes de simulations et du calcul de l'estimateur est prouvée. En particulier, quand les noeuds des B-splines sont variables, l'analyse bayésienne de la régression sous contrainte devient complexe. On propose des schémas de simulations originaux permettant de générer suivant la loi a posteriori lorsque la densité tronquée des coefficients de régression prend des dimensions variables. / We investigate the Bayesian regression under shape and smoothness constraints. We first elicita Bayesian method for regression under shape restrictions and smoothness conditions. Theregression function is built from B-spline basis that controls its regularity. Then we show thatits shape can be controlled simply from its coefficients in the B-spline basis. This is achievedthrough the control polygon whose definition and some properties are given in this article.The regression function is estimated by the posterior mode. This mode is calculated by asimulated annealing algorithm which allows to take into account the constraints of form inthe proposal distribution. A credible interval is obtained from simulations using Metropolis-Hastings algorithm with the same proposal distribution as the simulated annealing algorithm.The convergence of algorithms for simulations and calculation of the estimator is proved. Inparticular, in the case of Bayesian regression under constraints and with free knots, Bayesiananalysis becomes complex. we propose original simulation schemes which allows to simulatefrom the truncated posterior distribution with free dimension.

Cette thèse porte sur les espaces d'urbanisation dispersée de la métropole parisienne, c'est-à-dire des espaces bâtis discontinus, de taille petite et moyenne, insérés dans un tissu urbain lâche. Partant de l'offre commerciale, des pratiques associées et d'un ensemble de mobilités, cette thèse analyse ces espaces dans une approche relationnelle pour saisir les mécanismes qui sous-tendent les dynamiques des espaces d'urbanisation dispersée. L'approche s'inscrit dans le sillage des travaux récents qui opèrent un changement de focale en considérant ces espaces pour leurs caractéristiques propres et non par rapport aux espaces dominants des métropoles. L'enjeu est de proposer une vision critique sur la manière dont ils s'organisent au-delà des considérations et des représentations portées par les politiques et les aménageurs sur la dépendance et le déclin de ces espaces. La thèse développe une méthodologie mixte qui combine des approches quantitatives et la réalisation d'entretiens et de cartes mentales permettant de saisir les représentations des habitants dans quatre terrains. Le croisement des structures de peuplement et de la morphologie des espaces bâtis ont permis de mettre en évidence quatre formes contrastées de dispersion allant de la petite ville à l'habitat diffus. Le choix des terrains d'étude situés à moins de deux heures de Paris reflète cette diversité. Les espaces d'urbanisation dispersée ont été étudiés finement tout d'abord à partir de la structure commerciale et a montré une évolution contrastée du nombre de points de vente au regard de leurs fonctions au cours des quinze dernières années et une concentration des commerces dans les bourgs et les petites villes. Dans un deuxième temps, l'approche relationnelle a interpellé les liens qu'entretiennent ces espace: avec leur environnement et notamment avec Paris. Par cette analyse, elle met en avant la capacité de ces espaces à se structurer, à participer à des systèmes urbains et à s'inscrire dans des échanges réciproques et non univoques avec de grands pôles urbains. / This thesis deals with the scattered urbanization areas of the Paris metropolis. Combining the commercial offer, diversity of practice and mobilities, this thesis analyzes these areas in a relational approach to understand the mechanisms underlying their dynamics. We will approach the subject through the prism of recent works, using a new method that considers these areas for their own characteristics and not in relation to the dominant metropolis areas. The issue is to suggest a critical vision on the way they organize, beyond the traditional considerations and representations carried by politics and planners on the dependency and decline of these areas. Using a mixed methodology (quantitative approach, interview, and "mental maps"), we will try to understand the inhabitants' representations in 4 research areas. Four different types of dispersion from the small town to the scattered housing are highlighted, by crossing population patterns and built area morphology. The research fields are located within a two-hour drive from Paris and reflect this diversity. The scattered urbanization areas were finely studied starting with their commercial structure. We thus noticed a contrasted evolution in the number of stores and a concentration of shops in towns over the last 15 years. ln a second stage, the interpersonal approach focused on the links between these areas and their environment, particularly with Paris. Through this analysis, it highlights the capacity of these areas to be structured, to participate in urban systems and to be part of mutual exchanges with large regional hubs.

Dans cette thèse, j’aborde le problème important de l’estimation de la structure des réseaux complexes, à l’aide de la classe des modèles stochastiques dits réseaux Bayésiens. Les réseaux Bayésiens permettent de représenter l’ensemble des relations d’indépendance conditionnelle. L’apprentissage statistique de la structure de ces réseaux complexes par les réseaux Bayésiens peut révéler la structure causale sous-jacente. Il peut également servir pour la prédiction de quantités qui sont difficiles, coûteuses, ou non éthiques comme par exemple le calcul de la probabilité de survenance d’un cancer à partir de l’observation de quantités annexes, plus faciles à obtenir. Les contributions de ma thèse consistent en : (A) un logiciel développé en langage C pour l’apprentissage de la structure des réseaux bayésiens; (B) l’introduction d’un nouveau "jumping kernel" dans l’algorithme de "Metropolis-Hasting" pour un échantillonnage rapide de réseaux; (C) l’extension de la notion de réseaux Bayésiens aux structures incluant des boucles et (D) un logiciel spécifique pour l’apprentissage des structures cycliques. Notre principal objectif est l’apprentissage statistique de la structure de réseaux complexes représentée par un graphe et par conséquent notre objet d’intérêt est cette structure graphique. Un graphe est constitué de nœuds et d’arcs. Tous les paramètres apparaissant dans le modèle mathématique et différents de ceux qui caractérisent la structure graphique sont considérés comme des paramètres de nuisance. / In this thesis, I address the important problem of the determination of the structure of complex networks, with the widely used class of Bayesian network models as a concrete vehicle of my ideas. The structure of a Bayesian network represents a set of conditional independence relations that hold in the domain. Learning the structure of the Bayesian network model that represents a domain can reveal insights into its underlying causal structure. Moreover, it can also be used for prediction of quantities that are difficult, expensive, or unethical to measure such as the probability of cancer based on other quantities that are easier to obtain. The contributions of this thesis include (A) a software developed in C language for structure learning of Bayesian networks; (B) introduction a new jumping kernel in the Metropolis-Hasting algorithm for faster sampling of networks (C) extending the notion of Bayesian networks to structures involving loops and (D) a software developed specifically to learn cyclic structures. Our primary objective is structure learning and thus the graph structure is our parameter of interest. We intend not to perform estimation of the parameters involved in the mathematical models.

Radars operating at sea encounter a common phenomenon known as sea clutter, characterized by undesired reflections originating from the sea surface. This phenomenon can significantly impair the radar’s capacity to detect small, slow-moving targets. Therefore, it is crucial to gain a comprehensive understanding of the statistical attributes that describes the sea clutter. This comprehension is pivotal for the development of efficient signal processing strategies. The core of this work revolves around the imperative requirement for accurate statistical models to characterize sea clutter. Within this context, this work particularly explores the application of Field’s model. Field’s model describes the sea clutter process using three stochastic differential equations that form the dynamical process of the complex reflectivity of the sea surface. One equation describes the radar cross section, which is given by a Cox-Ingersoll-Ross process, parameterized by the parameters A and α. The other equations describe the speckle process, which is a complex Ornstein-Uhlenbeck process parameterized by B. The aim of this thesis is to explore the possibilities in estimating the parameters A, α and B in Field’s model through the application of Bayesian inference. To achieve this objective, Metropolis-Hastings and Sequential Monte Carlo methods are employed. The clutter data, represented by the complex reflectivity, is synthetically generated by using the Euler-Maruyma and Milstein schemes. Three algorithms are designed for estimating the sea clutter parameters. Two algorithms require 300 seconds of data and are based on the approach suggested by Clement Roussel in his PhD thesis [1]. Specifically, these algorithms employ the Metropolis-Hastings method for estimating A, α and B, respectively. As input data to the algorithms, estimators of the Cox-Ingersoll-Ross process and the real part of the Ornstein-Uhlenbeck process are utilized. In contrast, the last algorithm describes an approach that employs only 3 seconds of data. This algorithm is a Metropolis-Hastings method that incorporates a particle filter for approximation of likelihoods. For evaluation of the algorithms, two distinct sets of parameters are considered, leading to varying characteristics of the complex reflectivity. The two algorithms that require 300 seconds of data are ex- ecuted ten times for each parameter set. Evidently, the algorithm designed for estimating B generates values that closely aligns with the true values while the algorithm designed for estimating A and α does not yield as satisfactory results. Due to time constraints and the computational demands of the simulations, the last algorithm, requiring 3 seconds of data, is executed only twice for each parameter set. Remarkably, this algorithm generates estimates that agree with the true values, indicating strong performance. Nonetheless, additional simulations are required to conclusively confirm its robustness. To conclude, it is possible to estimate sea clutter parameters within Field’s model by using the applied methods of Bayesian inference. However, it is important to analyze the applicability of these methods for a large quantity of diverse clutter data. Moreover, their computational demands pose challenges in real-world applications. Future research should address the need for more computation- ally efficient methods to overcome this challenge. / Radar som verkar till havs behöver hantera ett fenomen som kallas för sjöklutter, vilket är oönskade reflektioner från havsytan. Detta fenomen kan avsevärt försämra radarns förmåga att upptäcka långsamt rörliga mål. Det är därför viktigt att erhålla en förståelse för den statistik som beskriver sjökluttret. Denna förståelse är avgörande för utvecklingen av effektiva signalbehandlingsstrategier. Detta arbete fokuserar på den viktiga aspekten av att använda korrekta statistiska modeller för att beskriva sjöklutter. Specifikt undersöker detta arbete Field’s modell, som beskriver den komplexa reflektiviteten från havsytan med hjälp av tre stokastiska differentialekvationer. En ekvation beskriver radarmålarean (radar cross section) som är en Cox-Ingersoll-Ross-process, parametriserad av A och α. De andra ekvationerna beskriver speckle-processen som är en komplex Ornstein-Uhlenbeck-process, parametriserad av B. Syftet med denna uppsats är att utforska möjligheter för att estimera parametrarna A, α och B i Field’s modell genom tillämpning av Bayesiansk inferens. För att uppnå detta, används Metropolis-Hastings-algoritmer samt sekventiella Monte-Carlo- metoder. Klotterdatan som representeras av den komplexa reflektiviteten genereras med hjälp av Euler-Maruyma- och Milstein-scheman. Sammanlagt designas tre algoritmer för att estimera sjöklutter- parametrarna. Två algoritmer behöver 300 sekunder av data och är baserade på tidigare arbeten av C. Rousell [1]. Dessa algoritmer använder Metropolis-Hastings för att uppskata B, respektive A och α. Som indata till algoritmerna används estimatorer för Cox-Ingersoll-Ross-processen samt den reella delen av Ornstein-Uhlenbeck-processen. Den sista algoritmen beskriver istället ett tillvägagångssätt som endast kräver 3 sekunders data. Denna algoritm är en Metropolis-Hastings-algoritm som använder ett partikelfilter för approximering av likelihoods. För utvärdering av algoritmerna beaktas två olika parameteruppsättningar, vilka genererar olika komplexa reflektiviteter. De två algoritmerna som kräver 300 sekunder av data körs tio gånger för varje parameteruppsättning. Algoritmen designad för att uppskatta B genererar värden som är nära de sanna värdena medan algoritmen designad för att uppskatta A och α inte ger lika tillfredsställande resultat. På grund av tidsbrist och den långa simuleringstiden, körs den sista algoritmen, som kräver 3 sekunder av data, endast två gånger för varje parameteruppsättning. Anmärkningsvärt är att denna algoritm genererar uppskattningar som faktiskt stämmer ganska väl med de sanna värdena, vilket indikerar på stark prestanda. Dock krävs ytterligare simuleringar för att bekräfta detta. Sammanfattningsvis är det möjligt att uppskatta sjöklutterparametrarna i Field’s model med de Bayesianska inferensmetoderna som tillämpas i detta arbete. Det är dock viktigt att beakta hur användbara dessa metoder är för en variation av klotterdata. Dessutom innebär den långa beräkningstiden utmaningar i verkliga tillämpningar. Framtida studier bör adressera behovet av mer beräkningsmässigt effektiva metoder för att övervinna denna utmaning.