The extent to which natural selection shapes diversity within populations is a key question for population genetics. Thus, there is considerable interest in quantifying the strength of selection. In this thesis a full likelihood approach for inference about selection at a single site within an otherwise neutral fully-linked sequence of sites is developed. Integral to many of the ideas introduced in this thesis is the reversibility of the diffusion process, and some past approaches to this concept are reviewed. A coalescent model of evolution is used to model the ancestry of a sample of DNA sequences which have the selected site segregating. A novel method for simulating the coalescent with selection, acting at a single biallelic site, is described. Selection is incorporated through modelling the frequency of the selected and neutral allelic classes stochastically back in time. The ancestry is then simulated using a subdivided population model considering the population frequencies through time as variable population sizes. The approach is general and can be used for any selection scheme at a biallelic locus. The mutation model, for the selected and neutral sites, is the infinitely-many-sites model where there is no back or parallel mutation at sites. This allows a unique perfect phylogeny, a gene tree, to be constructed from the configuration of mutations on the sample sequences. An importance sampling algorithm is described to explore over coalescent tree space consistent with this gene tree. The method is used to assess the evidence for selection in a number of data sets. These are as follows: a partial selective sweep in the G6PD gene (Verrelli et al., 2002); a recent full sweep in the Factor IX gene (Harris and Hey, 2001); and balancing selection in the DCP1 gene (Rieder et al., 1999). Little evidence of the action of selection is found in the data set of Verrelli et al. (2002) and the data set of Rieder et al. (1999) seems inconsistent with the model of balancing selection. The patterns of diversity in the data set of Harris and Hey (2001) offer support of the hypothesis of a full sweep.

In this paper we head for a fully Bayesian analysis of the latent class model with a priori unknown number of classes. Estimation is carried out by means of Markov Chain Monte Carlo (MCMC) methods. We deal explicitely with the consequences the unidentifiability of this type of model has on MCMC estimation. Joint Bayesian estimation of all latent variables, model parameters, and parameters determining the probability law of the latent process is carried out by a new MCMC method called permutation sampling. In a first run we use the random permutation sampler to sample from the unconstrained posterior. We will demonstrate that a lot of important information, such as e.g. estimates of the subject-specific regression coefficients, is available from such an unidentified model. The MCMC output of the random permutation sampler is explored in order to find suitable identifiability constraints. In a second run we use the permutation sampler to sample from the constrained posterior by imposing identifiablity constraints. The unknown number of classes is determined by formal Bayesian model comparison through exact model likelihoods. We apply a new method of computing model likelihoods for latent class models which is based on the method of bridge sampling. The approach is applied to simulated data and to data from a metric conjoint analysis in the Austrian mineral water market. (author's abstract) / Series: Forschungsberichte / Institut für Statistik

In the present paper we study switching state space models from a Bayesian point of view. For estimation, the model is reformulated as a hierarchical model. We discuss various MCMC methods for Bayesian estimation, among them unconstrained Gibbs sampling, constrained sampling and permutation sampling. We address in detail the problem of unidentifiability, and discuss potential information available from an unidentified model. Furthermore the paper discusses issues in model selection such as selecting the number of states or testing for the presence of Markov switching heterogeneity. The model likelihoods of all possible hypotheses are estimated by using the method of bridge sampling. We conclude the paper with applications to simulated data as well as to modelling the U.S./U.K. real exchange rate. (author's abstract) / Series: Forschungsberichte / Institut für Statistik

This paper presents the fully Bayesian analysis of the latent class model using a new approach towards MCMC estimation in the context of mixture models. The approach starts with estimating unidentified models for various numbers of classes. Exact Bayes' factors are computed by the bridge sampling estimator to compare different models and select the number of classes. Estimation of the unidentified model is carried out using the random permutation sampler. From the unidentified model estimates for model parameters that are not class specific are derived. Then, the exploration of the MCMC output from the unconstrained model yields suitable identifiability constraints. Finally, the constrained version of the permutation sampler is used to estimate group specific parameters. Conjoint data from the Austrian mineral water market serve to illustrate the method. (author's abstract) / Series: Report Series SFB "Adaptive Information Systems and Modelling in Economics and Management Science"

In this paper we head for a fully Bayesian analysis of the latent class model with a priori unknown number of classes. Estimation is carried out by means of Markov Chain Monte Carlo (MCMC) methods. We deal explicitely with the consequences the unidentifiability of this type of model has on MCMC estimation. Joint Bayesian estimation of all latent variables, model parameters, and parameters determining the probability law of the latent process is carried out by a new MCMC method called permutation sampling. In a first run we use the random permutation sampler to sample from the unconstrained posterior. We will demonstrate that a lot of important information, such as e.g. estimates of the subject-specific regression coefficients, is available from such an unidentified model. The MCMC output of the random permutation sampler is explored in order to find suitable identifiability constraints. In a second run we use the permutation sampler to sample from the constrained posterior by imposing identifiablity constraints. The unknown number of classes is determined by formal Bayesian model comparison through exact model likelihoods. We apply a new method of computing model likelihoods for latent class models which is based on the method of bridge sampling. The approach is applied to simulated data and to data from a metric conjoint analysis in the Austrian mineral water market. (author's abstract) / Series: Working Papers SFB "Adaptive Information Systems and Modelling in Economics and Management Science"

The dimploma thesis Comparison of AC and selection interview in process of employee selection in a bank institution is focused on comparison of financial, time and organizational difficulties of these two methods. The theoretic part defines basic terms as employee selection, Assessment Centre and selection interview. The Practical part compares process of selection in a bank institution for business positions. The thesis states time frame of each of the methods, defines invovled employees in processes, evaluates the processes according to costs and in the end copares results from selection interview which took place during AC and the overall results from AC.

Submitted by Vivian Raunheitti (vivian.raunheitti@fgv.br) on 2017-01-31T17:58:27Z No. of bitstreams: 1 UM DIAGNÓSTICO SOBRE A INFLUÊNCIA QUE OS DIFERENTES MODELOS DE SELEÇÃO EXERCEM SOBRE A DIFERENCIAÇÃO DE CANDIDATOS EM CONCURSOS PÚBLICOS.pdf: 1346833 bytes, checksum: a283cd7c9a2d3fb605223fa443cadee7 (MD5) / Approved for entry into archive by ÁUREA CORRÊA DA FONSECA CORRÊA DA FONSECA (aurea.fonseca@fgv.br) on 2017-02-02T17:44:35Z (GMT) No. of bitstreams: 1 UM DIAGNÓSTICO SOBRE A INFLUÊNCIA QUE OS DIFERENTES MODELOS DE SELEÇÃO EXERCEM SOBRE A DIFERENCIAÇÃO DE CANDIDATOS EM CONCURSOS PÚBLICOS.pdf: 1346833 bytes, checksum: a283cd7c9a2d3fb605223fa443cadee7 (MD5) / Made available in DSpace on 2017-02-09T13:59:34Z (GMT). No. of bitstreams: 1 UM DIAGNÓSTICO SOBRE A INFLUÊNCIA QUE OS DIFERENTES MODELOS DE SELEÇÃO EXERCEM SOBRE A DIFERENCIAÇÃO DE CANDIDATOS EM CONCURSOS PÚBLICOS.pdf: 1346833 bytes, checksum: a283cd7c9a2d3fb605223fa443cadee7 (MD5) Previous issue date: 2016-12-22 / The present work aims to evaluate the influence that different methods of selection exert over the differentiation of candidates in public examinations organized by FGV Projetos. Three stages were considered for this study: the objective written test, the discursive written test and the evaluation of titles. In the attempt towards deepening of public selection process, FGV Projetos has been formulating, in its exams, questions that require the necessary skills to perform a specific public function. In this sense, based on the obtained results, an individual and joint diagnosis of selection models currently applied were achieved The study also intends to be a guideline for the recruitment processes, establishing as a criterion of influence the weighted average of the grades of each stage of selection, the performance of one stage in relation to the other and the classification of the candidates on the final results. In order to achieve this, the candidates should undergo judicious evaluations, with different stages pertinent to the specifics of the position. The present work had a quali-quantitative nature, used a non-random sampling of the public examinations, realized by FGV Projects for the Administration area and adopted, as a data collection instrument, the documentary investigation of the opening announcements and the collection of secondary data of the results of 20 (twenty) selective processes executed and homologated between the years of 2013 and 2016. Finally, the socioeconomic and -demographic aspects of the candidates in comparison with their final position in the process were associated. The subjects of this study were those enrolled in the process who were present on the objective written test and / or the discursive written test, applying for Public Examinations for administrative areas, all of higher education level, segmented by the same field of knowledge. / O presente trabalho tem por objetivo avaliar a influência que os diferentes métodos de seleção exercem sobre a diferenciação dos candidatos nos concursos públicos organizados pela FGV Projetos. Foram consideradas para este estudo três etapas: a prova escrita objetiva, a prova escrita discursiva e a avaliação de títulos. A FGV Projetos, com o objetivo de contribuir na seleção de quadros públicos de qualidade, tem formulado, nos concursos por ela realizados, questões que exijam o conhecimento necessário acerca das competências para o exercício de determinada função pública. Nesse sentido, com base nos resultados obtidos, procurou-se realizar um diagnóstico isolado e conjugado dos modelos de seleção já aplicados. Esse estudo tem como intuito o aprofundamento do processo de seleção pública, estabelecendo como critério de influência a média ponderada das notas das etapas, do rendimento de uma etapa em relação à outra e da classificação dos candidatos sobre os resultados finais. Para atingir tal objetivo, os candidatos devem ser submetidos a avaliações criteriosas com etapas que possuam pertinência com as especificidades do cargo. O trabalho teve natureza quali-quantitativa, utilizou uma amostragem não-aleatória de concursos na área de Administração e adotou, como instrumento de coleta de dados, a investigação documental dos editais de abertura, e o levantamento de dados secundários dos resultados de 20 (vinte) processos seletivos executados e homologados entre os anos de 2013 e 2016. Por fim, foi avaliada a associação do perfil socioeconômico e demográfico dos candidatos sobre o processo de seleção. Os sujeitos desse estudo foram os inscritos que estavam presentes às provas escritas objetiva e/ou discursiva para os cargos da área de administração, todos de nível superior, segmentados pelos mesmos campos de conhecimento.

Diploma thesis is oriented for intake and selection of employees. Right selected worker can increase effectiveness of company and in that way he is one of the pivot elements of the organization. That’s why is necessary do not downgrade selection procedure and find perfect worker and then try to create conditions for two-sided satisfaction. Diploma thesis contains theoretic and practical part, which will be processed on base obtained from Center for leisure time Lužánky. The point is to design a new way of in taking employees which would lead to elevation of effectiveness and would get specific order to the whole selection procedure.

The thesis "Methods to Assess IS/ICT Outsourcing Models" focuses mainly on an assessment and selection process of suitable IS/ICT outsourcing models. First, IS/ICT outsourcing concept is explained and its advantages as well as disadvantages are described. Second, IS/ICT outsourcing models (primarily classified by outsourcing subject) and their characteristics are described. Third, existing methods to assess and subsequently select suitable IS/ICT outsourcing models are analysed. Main goal of the thesis is to confront the existing methods with a process used in real-life IS/ICT outsourcing project and then to give recommendations for methods improvement. To achieve that goal the existing methods are compared with a process used in the real-life outsourcing project. Based on positively perceived parts of the existing methods as well as on flaws identified, an own method to assess and select IS/ICT outsourcing models is designed. The following methods are used when writing the thesis: logical/historical method, description, analysis and synthesis. Main contribution of the thesis to the topic is a design of the own method aiming at improvements to the existing methods so that it is as usable as possible in practice. This is achieved through a design of tools supporting crucial steps of the designed method. The fact that the author is member of a project team working on the real-life IS/ICT outsourcing project facilitates a contribution achievement too.

Management and conservation of populations of animals requires information on where they are, why they are there, and where else they could be. These objectives are typically approached by collecting data on the animals’ use of space, relating these to prevailing environmental conditions and employing these relations to predict usage at other geographical regions. Technical advances in wildlife telemetry have accomplished manifold increases in the amount and quality of available data, creating the need for a statistical framework that can use them to make population-level inferences for habitat preference and space-use. This has been slow-in-coming because wildlife telemetry data are, by definition, spatio-temporally autocorrelated, unbalanced, presence-only observations of behaviorally complex animals, responding to a multitude of cross-correlated environmental variables. I review the evolution of techniques for the analysis of space-use and habitat preference, from simple hypothesis tests to modern modeling techniques and outline the essential features of a framework that emerges naturally from these foundations. Within this framework, I discuss eight challenges, inherent in the spatial analysis of telemetry data and, for each, I propose solutions that can work in tandem. Specifically, I propose a logistic, mixed-effects approach that uses generalized additive transformations of the environmental covariates and is fitted to a response data-set comprising the telemetry and simulated observations, under a case-control design. I apply this framework to non-trivial case-studies using data from satellite-tagged grey seals (Halichoerus grypus) foraging off the east and west coast of Scotland, and northern gannets (Morus Bassanus) from Bass Rock. I find that sea bottom depth and sediment type explain little of the variation in gannet usage, but grey seals from different regions strongly prefer coarse sediment types, the ideal burrowing habitat of sandeels, their preferred prey. The results also suggest that prey aggregation within the water column might be as important as horizontal heterogeneity. More importantly, I conclude that, despite the complex behavior of the study species, flexible empirical models can capture the environmental relationships that shape population distributions.