L'estimation du maximum de vraisemblance est une méthode répandue pour l'identification d'un modèle paramétré de série temporelle à partir d'un échantillon d'observations. Dans le cadre de modèles bien spécifiés, il est primordial d'obtenir la consistance de l'estimateur, à savoir sa convergence vers le vrai paramètre lorsque la taille de l'échantillon d'observations tend vers l'infini. Pour beaucoup de modèles de séries temporelles, par exemple les modèles de Markov cachés ou « hidden Markov models »(HMM), la propriété de consistance « forte » peut cependant être dfficile à établir. On peut alors s'intéresser à la consistance de l'estimateur du maximum de vraisemblance (EMV) dans un sens faible, c'est-à-dire que lorsque la taille de l'échantillon tend vers l'infini, l'EMV converge vers un ensemble de paramètres qui s'associent tous à la même distribution de probabilité des observations que celle du vrai paramètre. La consistance dans ce sens, qui reste une propriété privilégiée dans beaucoup d'applications de séries temporelles, est dénommée consistance de classe d'équivalence. L'obtention de la consistance de classe d'équivalence exige en général deux étapes importantes : 1) montrer que l'EMV converge vers l'ensemble qui maximise la log-vraisemblance normalisée asymptotique ; et 2) montrer que chaque paramètre dans cet ensemble produit la même distribution du processus d'observation que celle du vrai paramètre. Cette thèse a pour objet principal d'établir la consistance de classe d'équivalence des modèles de Markov partiellement observés, ou « partially observed Markov models » (PMM), comme les HMM et les modèles « observation-driven » (ODM). / Maximum likelihood estimation is a widespread method for identifying a parametrized model of a time series from a sample of observations. Under the framework of well-specified models, it is of prime interest to obtain consistency of the estimator, that is, its convergence to the true parameter as the sample size of the observations goes to infinity. For many time series models, for instance hidden Markov models (HMMs), such a “strong” consistency property can however be difficult to establish. Alternatively, one can show that the maximum likelihood estimator (MLE) is consistent in a weakened sense, that is, as the sample size goes to infinity, the MLE eventually converges to a set of parameters, all of which associate to the same probability distribution of the observations as for the true one. The consistency in this sense, which remains a preferred property in many time series applications, is referred to as equivalence-class consistency. The task of deriving such a property generally involves two important steps: 1) show that the MLE converges to the maximizing set of the asymptotic normalized loglikelihood; and 2) show that any parameter in this maximizing set yields the same distribution of the observation process as for the true parameter. In this thesis, our primary attention is to establish the equivalence-class consistency for time series models that belong to the class of partially observed Markov models (PMMs) such as HMMs and observation-driven models (ODMs).

The thesis focuces on project documentation for a construction project with the aim to design home for children under institutional care. Located on the outskirts of Skuteč, the building is three-storey, detached and partially basemented. The basement area lays on the slab foundations and the first floor on strip foundations. Vertical structures are made of ceramic blocks and local reinforced concrete columns while horizontal structures are made of reinforced concrete slabs and wooden trusses over the gym. The building is covered by a vegetated flat roof. The building houses six residential units for six family groups with a total capacity of 43 children. The basement includes gym and fitness with technical facilities. The first floor consists of three residential units, changing rooms for the gym and kitchen with facilities. The second floor houses remaining three residential units, offices and the refectory. The upper floor is used for children´s education and entertainment.

Quasi-hereditary algebras are an important class of algebras with many appli-cations in representation theory, most notably the representation theory of semi-simple complex Lie-algebras. Such algebras sometimes admit an exact Borel sub-algebra, that is a subalgebra satisfying similar formal properties to the Borel sub-algebras from Lie theory. This thesis is divided into two parts. In the first part we classify quasi-hereditary algebras with two simple modules over perfect fields up to Morita equivalence, generalizing a similar result by Membrillo-Hernandez for thealgebraically closed case. In the second part, we take a poset X, a certain set M of constants, and a finite set ρ of paths in the Hasse-diagram of X and construct analgebra A(X, M, ρ) that generalizes the twisted double incidence algebras originally introduced by Deng and Xi. We provide necessary and sufficient conditions for this algebra to be quasi-hereditary when X is a tree, and we show that A(X, M, ρ) admits an exact Borel subalgebra when these conditions are satisfied. Following this, we compute the Ext-algebra of the standard modules of A(X, M, ρ).

Indiana University-Purdue University Indianapolis (IUPUI) / Learning in Partially Observable Markov Decision process (POMDP) is motivated by the essential need to address a number of realistic problems. A number of methods exist for learning in POMDPs, but learning with limited amount of information about the model of POMDP remains a highly anticipated feature. Learning with minimal information is desirable in complex systems as methods requiring complete information among decision makers are impractical in complex systems due to increase of problem dimensionality. In this thesis we address the problem of decentralized control of POMDPs with unknown transition probabilities and reward. We suggest learning in POMDP using a tree based approach. States of the POMDP are guessed using this tree. Each node in the tree has an automaton in it and acts as a decentralized decision maker for the POMDP. The start state of POMDP is known as the landmark state. Each automaton in the tree uses a simple learning scheme to update its action choice and requires minimal information. The principal result derived is that, without proper knowledge of transition probabilities and rewards, the automata tree of decision makers will converge to a set of actions that maximizes the long term expected reward per unit time obtained by the system. The analysis is based on learning in sequential stochastic games and properties of ergodic Markov chains. Simulation results are presented to compare the long term rewards of the system under different decision control algorithms.

Purpose: The purpose of this study is to identify how uncertainties affect a partially distributed team. To do this, the thesis goes into the details of the different types of uncertainties and how they are handled. Design/Methodology/Approach: This research uses a multiple case study with interviews and observations as data gathering methods. The two cases study are first analyzed separately and then a cross case analysis is conducted. Findings: This study showed that uncertainties are mostly correlated to threats and therefor focus lies on mitigating them. Using agile practices allows for a greater flexibility and makes uncertainties more manageable. Practical implications: This study shows the value of following agile principles. It also shows that when choosing to have a partially distributed team one needs to weigh the negative aspects with the positive ones. Originality/Value: This study combines research conducted on partially distributed teams and uncertainties. / Syfte: Syftet med denna studie är att identifiera hur osäkerheter påverkar ett delvis distribuerat team. För att göra detta går uppsatsen in i detalj om olika typer av osäkerheter och hur de kan hanteras. Design/Metodologi/Ansats: Denna studie använder sig av fallstudier med intervjuer och observationer som datainsamlingsmetoder. Två fallstudier analyseras först separat och därefter genomförs en korsfallsanalys. Resultat: Denna studie visade att osäkerheter mestadels är korrelerade med hot och därför ligger fokus på att förhindra dem. Genom att använda agila metoder möjliggörs större flexibilitet och gör osäkerheter mer hanterbara. Praktisk betydelse: Denna studie visar värdet av att följa agila principer. Det visar också att när man väljer att ha ett delvis distribuerat team måste man väga de negativa aspekterna med de positiva. Orginalitet/Värde: Denna studie kombinerar forskning som utförs på delvis distribuerade team och osäkerheter.

Greenhouse gas emissions are one of the critical factors that affect climate change, increasing flooding risk and threatening human life. The use of traditional construction materials is responsible for a higher percentage of global greenhouse gas emissions when compared to the use of sustainable materials in the construction industry. The substitution of current building materials with sustainable materials is essential to reduce greenhouse gas emissions and positively influence climate change when the current construction demand in the world is considered. Wood is one of the primary environmentally friendly construction materials in regard to high carbon storage and low carbon emissions. Cross-laminated timber (CLT) is prefabricated and this type of composite wood material is convenient for constructing middle to high rise buildings because materials are able to be cut to specific specifications which lowers onsite labor time. This research observed the hygrothermal behavior of partially submerged CLT wall panels during the wetting and drying period and simulated the flooding of the panels with a software tool, Wärme Und Feuchte Instationär (WUFI). The higher number of CLT layers caused a slower water penetration rate throughout the layers with a lower water absorption rate corresponding to the first layer than the other layers, so the water was primarily retained in the first layer. Also, water penetration through axial direction significantly decreased due to gravity impact when the height of CLT panels was increased. The visual assessment showed that the 3-day-wetted CLT panel configurations did not show any type of fungi growth through the wetting and drying period. However, both untreated and treated CLT panels with the envelope system did have fungi growth on the drywall after a 20-day-wetting period.

Die Quantilsregression untersucht die Quantilfunktion QY |X (τ ), sodass ∀τ ∈ (0, 1), FY |X [QY |X (τ )] = τ erfu ̈llt ist, wobei FY |X die bedingte Verteilungsfunktion von Y gegeben X ist. Die Quantilsregression ermo ̈glicht eine genauere Betrachtung der bedingten Verteilung u ̈ber die bedingten Momente hinaus. Diese Technik ist in vielerlei Hinsicht nu ̈tzlich: beispielsweise fu ̈r das Risikomaß Value-at-Risk (VaR), welches nach dem Basler Akkord (2011) von allen Banken angegeben werden muss, fu ̈r ”Quantil treatment-effects” und die ”bedingte stochastische Dominanz (CSD)”, welches wirtschaftliche Konzepte zur Messung der Effektivit ̈at einer Regierungspoli- tik oder einer medizinischen Behandlung sind. Die Entwicklung eines Verfahrens zur Quantilsregression stellt jedoch eine gro ̈ßere Herausforderung dar, als die Regression zur Mitte. Allgemeine Regressionsprobleme und M-Scha ̈tzer erfordern einen versierten Umgang und es muss sich mit nicht- glatten Verlustfunktionen besch ̈aftigt werden. Kapitel 2 behandelt den Einsatz der Quantilsregression im empirischen Risikomanagement w ̈ahrend einer Finanzkrise. Kapitel 3 und 4 befassen sich mit dem Problem der h ̈oheren Dimensionalit ̈at und nichtparametrischen Techniken der Quantilsregression. / Quantile regression studies the conditional quantile function QY|X(τ) on X at level τ which satisfies FY |X QY |X (τ ) = τ , where FY |X is the conditional CDF of Y given X, ∀τ ∈ (0,1). Quantile regression allows for a closer inspection of the conditional distribution beyond the conditional moments. This technique is par- ticularly useful in, for example, the Value-at-Risk (VaR) which the Basel accords (2011) require all banks to report, or the ”quantile treatment effect” and ”condi- tional stochastic dominance (CSD)” which are economic concepts in measuring the effectiveness of a government policy or a medical treatment. Given its value of applicability, to develop the technique of quantile regression is, however, more challenging than mean regression. It is necessary to be adept with general regression problems and M-estimators; additionally one needs to deal with non-smooth loss functions. In this dissertation, chapter 2 is devoted to empirical risk management during financial crises using quantile regression. Chapter 3 and 4 address the issue of high-dimensionality and the nonparametric technique of quantile regression.

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