<p>Syftet med uppsatsen är att försöka förklara vad det är som påverkar tiden som en mamma ammar. För att undersöka vad det är som påverkar tiden som en mamma ammar, har en Zero inflated negative binomial-modell (ZINB-modell) tagits fram. Resultaten visar att det som avgör hur länge en mamma kommer att amma är: Graviditetens längd, mammans ålder, mammans rökvanor under graviditetens sista månader, mammans rökvanor samt mammans nationella ursprung.</p>

Syftet med uppsatsen är att försöka förklara vad det är som påverkar tiden som en mamma ammar. För att undersöka vad det är som påverkar tiden som en mamma ammar, har en Zero inflated negative binomial-modell (ZINB-modell) tagits fram. Resultaten visar att det som avgör hur länge en mamma kommer att amma är: Graviditetens längd, mammans ålder, mammans rökvanor under graviditetens sista månader, mammans rökvanor samt mammans nationella ursprung.

Many state agencies consider exclusive truck facilities to be an alternative to handle the safety and operational issues due to the increasing truck volumes. No such facilities exist, and there are no standard tools or procedures for measuring safety performance of an exclusive truck facility. This thesis aims at identifying factors that affect truck crashes, whose results could be used for better designing exclusive truck facilities. To accomplish the objectives of this thesis, five years’ roadway and crash data for Texas was collected to develop a comprehensive crash database. Negative binomial regression models were used to establish a relationship between truck crashes and various environmental, geometric and traffic variables. Separate models were developed for truck-related (involving at least one truck and another vehicle), truck-only (two trucks or more) and single-truck crashes. The results suggested that the percentage of trucks in Average Annual Daily Traffic (AADT), classification of the roadway (Rural/Urban), posted speed limit, surface condition, alignment and shoulder width are associated with truck crashes. It was observed that truck-related and truck-only crashes decreased as the percentage of trucks increased on freeway facilities. Based on conclusions derived from the literature review and statistical analyses, straight segments with wider shoulders and uniform grades are recommended for exclusive truck facilities. It is also recommended to provide ramps, horizontal and vertical curvature and signing based on truck size, driver eye height, braking ability and maneuverability. These models were developed using mixed-flow traffic data to understand the association of various factors with truck crashes. These models should not be used directly to estimate or predict truck crashes. Further analysis with more detailed data under different flow conditions might help in quantifying the safety performance of exclusive truck facilities.

In this thesis, first we replace the condition X ¡Ø y in Huang and Su (2000) by X ¡Ù y and give necessary and sufficient conditions such that there exists a random variable X satisfying that E(g(X)| X ¡Ø y)=h(y) f(y )/ F(y), " y &#x00CE; CX, where CX is the support of X.Next, we investigate necessary and sufficient conditions such that h(y)=E(g(X) | X ¡Ø y ), for a given function h and extend these results to bivariate case.

Many state agencies consider exclusive truck facilities to be an alternative to handle the safety and operational issues due to the increasing truck volumes. No such facilities exist, and there are no standard tools or procedures for measuring safety performance of an exclusive truck facility. This thesis aims at identifying factors that affect truck crashes, whose results could be used for better designing exclusive truck facilities. To accomplish the objectives of this thesis, five years' roadway and crash data for Texas was collected to develop a comprehensive crash database. Negative binomial regression models were used to establish a relationship between truck crashes and various environmental, geometric and traffic variables. Separate models were developed for truck-related (involving at least one truck and another vehicle), truck-only (two trucks or more) and single-truck crashes. The results suggested that the percentage of trucks in Average Annual Daily Traffic (AADT), classification of the roadway (Rural/Urban), posted speed limit, surface condition, alignment and shoulder width are associated with truck crashes. It was observed that truck-related and truck-only crashes decreased as the percentage of trucks increased on freeway facilities. Based on conclusions derived from the literature review and statistical analyses, straight segments with wider shoulders and uniform grades are recommended for exclusive truck facilities. It is also recommended to provide ramps, horizontal and vertical curvature and signing based on truck size, driver eye height, braking ability and maneuverability. These models were developed using mixed-flow traffic data to understand the association of various factors with truck crashes. These models should not be used directly to estimate or predict truck crashes. Further analysis with more detailed data under different flow conditions might help in quantifying the safety performance of exclusive truck facilities.

This research assesses the performance of over-dispersed Poisson regression model and negative binomial model with count data. It examines the association between price plan features of mobile phone services and the number of people who adopt the plan. Mobile service data is used to estimate the model with a sample of one million customers running from February 2006 to September 2009. Under three main categories, customer type, age, and handset price, we run the model based on price plan features. Estimates are derived from the maximum likelihood estimation (MLE) method. Root mean squared error (RMSE) is used to observe the statistical fits of all the regression models. Then, we construct four estimation and holdout samples, leaving out one, three, six, and twelve months. The estimation constitutes the in-sample (IS) and the holdout represents the out-sample (OS). By estimating the IS, we predict the OS. Root mean squared error of prediction (RMSEP) is checked to see how accurate the prediction is. Results generally suggest that academic year start (AYS), seasonality, duration of months since launch of price plan (DMLP), basic fees, rate with no discount (RND), free call minutes (FCM), free data (FD), free text messaging (FTM), free perk rating (FPR), and handset support all show significant effect. The significance occurs depending on the segment. The RMSE and RMSEP show that the over-dispersed Poisson model outperforms the negative binomial model. Further implications and limitations of the results are discussed. / text

Las diapositivas contienen algunas distribuciones especiales de probabilidad como las siguientes: geométrica, Pascal y exponencial.

We consider weak convergence of a sequence of asset price models (Sn) to a limiting asset price model S. A typical case for this situation is the convergence of a sequence of binomial models to the Black-Scholes model, as studied by Cox, Ross, and Rubinstein. We put emphasis on two different aspects of this convergence: firstly we consider convergence with respect to the given "physical" probability measures (Pn) and secondly with respect to the "risk-neutral" measures (Qn) for the asset price processes (Sn). (In the case of non-uniqueness of the risk-neutral measures also the question of the "good choice" of (Qn) arises.) In particular we investigate under which conditions the weak convergence of (Pn) to P implies the weak convergence of (Qn) to Q and thus the convergence of prices of derivative securities. The main theorem of the present paper exhibits an intimate relation of this question with contiguity properties of the sequences of measures (Pn) with respect to (Qn) which in turn is closely connected to asymptotic arbitrage properties of the sequence (Sn) of security price processes. We illustrate these results with general homogeneous binomial and some special trinomial models. (author's abstract) / Series: Report Series SFB "Adaptive Information Systems and Modelling in Economics and Management Science"

As one of the major data analysis methods, statistical models play an important role in traffic safety analysis. A common situation associated with crash data is the phenomenon known as overdispersion which has been discussed and investigated frequently in recent years. As such, researchers have proposed several models, such as the Poisson Gamma (PG) or Negative Binomial (NB), the Poisson-lognormal, or the Poisson-Weibull, to handle the overdispersion. Unfortunately, very few models have been proposed for specifically analyzing the sources of dispersions in the data. Better understanding of sources of variation and overdispersion could help in managing safety, such as establishing relationships and applying appropriate treatments or countermeasures, more efficiently. Given the limitations of existing models for exploring the source of overdispersion of crash data, this research examined a new model function that could be applied to explore sources of extra variability through the use of the Generalized Waring (GW) models. This model, which was recently introduced by statisticians, divides the observed variability into three components: randomness, internal differences between road segments or intersections, and the variances caused by other external factors that have not been included as covariates in the model. To evaluate these models, GW models were examined using both simulated and empirical crash datasets, and the results were compared to the most commonly used NB model and the recently developed NB-Lindley models. For model parameter estimation, both the maximum likelihood method and a Bayesian approach were adopted for better comparison. A simulation study was used to show the better performance of this model compared to NB model for overdispersed data, and then an application in the empirical crash data illustrates its capability of modeling data sets with great accuracy and exploring the source of overdispersion. The performances of hotspot identification for these two kinds of models (i.e., GW models and NB models) were also examined and compared based on the estimated models from the empirical dataset. Finally, bias properties related to the choice of prior distributions for parameters in GW model were examined by using a simulation study. In addition, the suggestions on the choice of minimum sample size and priors were presented for different kinds of datasets.

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UFVJM n?o ? ag?ncia financiadora Verificar nome Carlos Alberto Mirez Tarrillo se ? espanhol. on 2018-04-20T15:06:05Z (GMT) / Submitted by Raniere Barreto (raniere.barros@ufvjm.edu.br) on 2018-05-15T19:08:56Z No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) bruno_ferreira_campos_silva.pdf: 2957468 bytes, checksum: 54576f6c332d9ba048e85d7de08b09a8 (MD5) / Approved for entry into archive by Rodrigo Martins Cruz (rodrigo.cruz@ufvjm.edu.br) on 2018-05-15T19:50:24Z (GMT) No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) bruno_ferreira_campos_silva.pdf: 2957468 bytes, checksum: 54576f6c332d9ba048e85d7de08b09a8 (MD5) / Made available in DSpace on 2018-05-15T19:50:24Z (GMT). No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) bruno_ferreira_campos_silva.pdf: 2957468 bytes, checksum: 54576f6c332d9ba048e85d7de08b09a8 (MD5) Previous issue date: 2017 / Nesta disserta??o ? apresentada a teoria que envolve o modelo de Black ? Scholes como uma alternativa de investimento para produtores rurais dos Vales do Jequitinhonha e Mucuri. Ao fazer um estudo sobre os produtores rurais dos vales, percebe-se que a produ??o no campo ? voltada para a subsist?ncia, vendendo somente o excedente. Foi constatado que a falta de investimento no campo reduz em partes o n?vel de produ??o do produtor rural. A alternativa de investimento atrav?s do modelo de Black ? Scholes na precifica??o de op??es se faz necess?rio n?o somente para se ter um maior investimento no meio rural, mas sim, ser tamb?m uma outra forma de se obter renda com t?cnicas aplicadas na Bolsa de Valores, ajudando o homem do campo em ter uma estabilidade financeira baseada n?o somente em sua produ??o. ? realizado um estudo criterioso da equa??o diferencial parcial estoc?stica advinda deste modelo, no tocante ? determina??o de poss?veis simula??es de problemas enfrentados diante das volatilidades dos mercados na precifica??o de op??es. Para que o produtor rural utilize o modelo de Black ? Scholes ? interessante se observar como se comporta os seus par?metros. Ent?o foi realizado uma an?lise do comportamento do valor da precifica??o de op??es em rela??o aos par?metros do modelo de Black ? Scholes baseados em dados reais retirados da BM&FBOVESPA. ? apresentada uma breve compara??o do modelo de Black ? Scholes com o modelo Binomial, compara??o feita com um exemplo de obten??o do valor da op??o de compra e venda via Binomial e Black ? Scholes, e neste exemplo ? observado um melhor retorno para o modelo Binomial. ? observado ao longo da pesquisa que existem dois par?metros que mais oscilam nos mercados, que s?o a volatilidade e a taxa de juros. Para se fazer bons investimentos, o produtor rural deve ficar atento e ter ci?ncia do comportamento da oscila??o desses par?metros. Para se ter uma melhor representa??o da varia??o desses par?metros, ? feito uma compara??o entre o valor das op??es de compra e venda calculados pelo modelo de Black ? Scholes e Binomial. Para a taxa de juros o modelo Binomial apresentou valores fora do esperado em rela??o ao modelo de Black ? Scholes. Devido a car?ncia de informa??es a respeito de como se investir na Bolsa de Valores, ? criado uma cartilha que se encontra nos anexos desta disserta??o voltada para o produtor rural, sobre como fazer um investimento na Bolsa de Valores e quais procedimentos iniciais deve-se tomar para obter ?xito nos mercados. Desses estudos, conclui-se que ? poss?vel o produtor rural investir pequenas quantias de dinheiro e obter retornos significativos em rela??o ao investimento inicial. Podendo assim, aplicar parte desse dinheiro em seu trabalho no campo e tamb?m ter uma forma de renda quando os retornos das produ??es no meio rural n?o forem favor?veis. / Disserta??o (Mestrado Profissional) ? Programa de P?s-Gradua??o em Tecnologia, Sa?de e Sociedade, Universidade Federal dos Vales do Jequitinhonha e Mucuri, 2017. / In this dissertation there is presented the theory that involves the Black model ? Scholes as an alternative of investment for rural producer Jequitinhonha and Mucuri Valleys. When doing a study on the rural producers of the valleys, it is seen that the production in the field is turned for the subsistence, selling only the excess. It was noted that the lack of investment in the field reduces in parts the level of production of the rural producer. The investment alternative through Black model ? Scholes in the options pricing is made necessary not only in order that a bigger investment has been in the rural environment, but yes, to be also another form of income being obtained with techniques applied in the valuable Stock Exchange, helping the man of the field in having a financial stability based not only on his production. It is accomplished out a discerning study of the partial differential equation stochastic resulted from this model, regarding the determination of possible simulations of problems faced before the volatilities of the markets in the options pricing. For the rural producer to use the Black model ? Scholes is interesting it will notice how if it holds his parameters. Then there was accomplished out an analysis of the behavior of the value of the pricing of options regarding the parameters of the Black model ? Scholes based on retired real data of the BM&FBOVESPA. There is presented a short comparison of the Black model ? Scholes with the Binominal model, comparison done with an example of getting the value of the option of purchase and sale was seeing Binomial and Black ? Scholes, and in this example a better return is observed for the Binomial model. It is observed throughout the research that there are two parameters that more oscillate in the markets, which are the volatility and the interest rate. In order that good investments become, the rural producer must be attentive and have science of the behavior of the oscillation of these parameters. In order that there has been a better representation of the variation of these parameters, it is done a comparison between the value of the options of purchase and sale calculated by the Black model ? Scholes and Binomial. For the interest rate the Binomial model presented values out of the waited one regarding the Black model ? Scholes. Due to lack of information about how to invest in the Stock Exchange, it is created a primer that is in the annexes of this dissertation turned to the rural producer how to make an investment in the Stock Exchange and it is necessary to take which initial proceedings to obtain succeed in the markets. Of these studies, it is ended that the possible the rural producer to invest small amounts of money and to obtain significant returns regarding the initial investment. Being able so, to apply part of this money in his work in the field and also to have the form of income when the returns of the productions in the rural environment are not favorable.