This thesis sheds light on the political motivations that lay at the basis of the dogmatic condemnations of Salafi Wahhabis of demonstrations against unjust Muslim rulers as engineered by Ash'aris....Show moreThis thesis sheds light on the political motivations that lay at the basis of the dogmatic condemnations of Salafi Wahhabis of demonstrations against unjust Muslim rulers as engineered by Ash'aris. It consults an enormous number of primary sources on which the selective justification of Salafi Wahhabis base these dogmatic condemnations of their Ash'ari components. As a result, the dogmatic condemnation by Salafi Wahhabis of Ash'aris as innovators due to the latter's justification of demonstrating against the unjust ruler is put in an international political context.Show less
Documentaries have a history of being the mouthpiece of the Chinese government; an important medium to present a good image of the country. The Party knows that at the same time a critical...Show moreDocumentaries have a history of being the mouthpiece of the Chinese government; an important medium to present a good image of the country. The Party knows that at the same time a critical documentary can do harm. Nevertheless, especially economic reasons have made the government less rigid on documentary making—the times that the only documentaries in the country were pure Party propaganda is over. Internet has been another influence that weakened Party control. Crowdfunding gives the crowd the possibility to gather together, share ideas and financially support the creation of products. Although through crowdfunding of documentaries a different voice can be heard, the existence of these websites does of course not mean the disappearance of censorship. Therefore we cannot expect a big shift in the democratic potential of documentaries just because of the better possibilities for active audience participation through crowdfunding. Research on recent prohibited documentaries showed most of the banned documentaries regard suppression by the government of citizen rights: the government wants to prevent an upsurge of social tensions. The fact that the documentaries of the case study that address social issues are allowed to be shown across the country backs this. Crowdfunding in China thus does offer more people the opportunity to voice their opinion through documentaries, also critical opinions, but it does not increase the democratic potential in Chinese documentary art.Show less
An edition of a treatise on the Ten Commandments based on Princeton, University Library, Garrett 143, fols. 1r-22v, one, as yet unpublished, of the twenty-seven versions of treatises on the Ten...Show moreAn edition of a treatise on the Ten Commandments based on Princeton, University Library, Garrett 143, fols. 1r-22v, one, as yet unpublished, of the twenty-seven versions of treatises on the Ten Commandments still extant. The aim of this edition is to offer insight into the many distinctive elements that may be involved in an edition rather than just the philological side to editing.Show less
The Three Kingdoms hero Guan Yu has long been a very interesting subject of study due to his gradual rise from the status of tragic hero to that of deity. Over the course of this image-building...Show moreThe Three Kingdoms hero Guan Yu has long been a very interesting subject of study due to his gradual rise from the status of tragic hero to that of deity. Over the course of this image-building process he has accumulated a number of different titles and functions. This thesis seeks to contrast this image has taken shape through the literary and religious realms in which he played a role.Show less
In this study the performance of feature-based dissimilarity space(FDS) classification is evaluated by comparing it to conventional classification techniques. In FDS classification a classifier is...Show moreIn this study the performance of feature-based dissimilarity space(FDS) classification is evaluated by comparing it to conventional classification techniques. In FDS classification a classifier is trained by using a dissimilarity space instead of a feature vector space. Since FDS classification is applied in a wide range of classifiers a new and model independent dissimilarity feature selection method is presented and tested. The fundamentals of this newly proposed selection method are given by the compactness hypothesis(Arkadev and Braverman, 1966). The performance of this newly proposed dissimilarity feature selection technique is evaluated by a Monto-Carlo simulation experiment and a bootstrap study. The performance of FDS classification is evaluated by comparing it to the performance of conventional classification techniques. The performance of FDS classification is estimated by using a bootstrap procedure. The results indicate that FDS classification is beneficial in combination with a linear classifier and a complex classification task. Due to the combination of a linear classifier and FDS classification a linear decision boundary is fitted in a dissimilarity space. This decision boundary becomes non-linear in the original feature vector space.Show less
Medical researchers frequently make statements that one model predicts survival better than another, and are frequently challenged to provide rigorous statistical justification for these statements...Show moreMedical researchers frequently make statements that one model predicts survival better than another, and are frequently challenged to provide rigorous statistical justification for these statements. In general, it is important to quantify how well the model is able to distinguish between high risk and low risk subjects (discrimination), and how well the model predicts the probability of having experienced the event of interest prior to a specified time t (predictive accuracy). For ordinary – right censored – survival data, the two most popular methods for discrimination and predictive accuracy are the concordance index, or c-index (Harrell et al. 1986) and the prediction error based on the Brier score (Graf et al. 1999). In the absence of censoring, it is straightforward to define and estimate these measures. Adaptations of these simple estimates for right censored survival data have been proposed and are now in common use. The novel part of this thesis is to develop methods for calculating/estimating the concordance index and the Brier score prediction error in the context of interval censored survival data. The starting point is that we have interval censored data of the form (Li , Ri ] for subjects i = 1, ..., n, with Li < Ri(Li may be 0, Ri may be infinity to accommodate right censored data), and a given prediction model yielding a single (estimated) baseline hazard h0(t), one vector of (estimated) regression coefficients beta. From this prediction model, prognostic scores β T xi , and predicted survival probabilities S(t|xi) = exp(−H0(t)β T xi), may be calculated for each subject i. Methods to estimate the concordance index and the Brier score prediction error for exponential and Weibull baseline hazards are proposed and evaluated in a simulation study. An application to real data is also provided.Show less
In the world of clustering methodology, there exists a plethora of options. The choice becomes especially important when the number of clusters is not known a priori. Methods to handle missing data...Show moreIn the world of clustering methodology, there exists a plethora of options. The choice becomes especially important when the number of clusters is not known a priori. Methods to handle missing data also have vast variation and these choices are often made based on the data missing mechanism. In this paper we seek to investigate the intersection of both these situations: Clustering, where one of the major objectives is cluster discovery, and doing so in the presence of missing values. Model-based clustering estimates the structure of clusters, (number, size and distribution of clusters) using likelihood approaches. Likelihood methods also allow researchers to gain information from incomplete observations. In the following work, we will investigate adaptations of these likelihood estimations to infer cluster information about a given data set. Model-based clustering becomes the focal point because of the objectivity in cluster discovery, and for continuous data, its multivariate Gaussian density assumptions can be an asset to handling the problem of missing data. An algorithm that utilises marginal multivariate Gaussian densities for assignment probabilities, was developed and tested versus more conventional ways of model-based clustering for incomplete data. These conventional methods included multiple imputation and using complete observations only. Assumptions of the data missing mechanism were important and taken into consideration during the testing of these methods. These assumptions were especially important for the model-based method when parameters had to be updated. All methods were tested using simulated data as well as real life publicly available data. It was found that for cases with many observations, the complete case and multiple imputation have advantages over the marginal density method due to the increased availbiltity of disposable information and borrowable information respectively. Dimensionality and cluster separation were also important factors. Multiple Imputation was the preferred method when our data structure was more complicated (high dimensions, high cluster overlap), however in simpler settings, the marginal method worked best. The marginal method also showed significant promise in classifying observations to their clusters. The marginal method can be further adapted by making more robust parameter estimates and is discussed in this paper.Show less
