990 resultados para Empirical Functions


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Background: In longitudinal studies where subjects experience recurrent incidents over a period of time, such as respiratory infections, fever or diarrhea, statistical methods are required to take into account the within-subject correlation. Methods: For repeated events data with censored failure, the independent increment (AG), marginal (WLW) and conditional (PWP) models are three multiple failure models that generalize Cox"s proportional hazard model. In this paper, we revise the efficiency, accuracy and robustness of all three models under simulated scenarios with varying degrees of within-subject correlation, censoring levels, maximum number of possible recurrences and sample size. We also study the methods performance on a real dataset from a cohort study with bronchial obstruction. Results: We find substantial differences between methods and there is not an optimal method. AG and PWP seem to be preferable to WLW for low correlation levels but the situation reverts for high correlations. Conclusions: All methods are stable in front of censoring, worsen with increasing recurrence levels and share a bias problem which, among other consequences, makes asymptotic normal confidence intervals not fully reliable, although they are well developed theoretically.

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One of the most important problems in optical pattern recognition by correlation is the appearance of sidelobes in the correlation plane, which causes false alarms. We present a method that eliminate sidelobes of up to a given height if certain conditions are satisfied. The method can be applied to any generalized synthetic discriminant function filter and is capable of rejecting lateral peaks that are even higher than the central correlation. Satisfactory results were obtained in both computer simulations and optical implementation.

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Mergers and acquisitions (M&A) have played very important role in restructuring the pulp and paper industry (PPI). The poor performance and fragmented nature of the industry, overcapacity problems, and globalisation have driven companies to consolidate. The objective of this thesis was to examine how PPI acquirers’ have performed subsequent M&As and whether the deal characteristics have had any impact on performance. Based on the results it seems that PPI companies have not been able to enhance their performance in the long run after M&As although the per-formance of acquiring firms has remained above the industry median, and deal characteristics or the amount of premiums paid do not seem to have had any effect. The statistical significance of the results was tested with change model and regression analysis. Performance was assessed with accrual, cash flow, and market based indicators. Results are congruent with behavioural theory: managers and investors seem to be overoptimistic in determining the synergies from M&As.

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Regulation has in many cases been delegated to independent agencies, which has led to the question of how democratic accountability of these agencies is ensured. There are few empirical approaches to agency accountability. We offer such an approach, resting upon three propositions. First, we scrutinize agency accountability both de jure (accountability is ensured by formal rights of accountability 'fora' to receive information and impose consequences) and de facto (the capability of fora to use these rights depends on resources and decision costs that affect the credibility of their sanctioning capacity). Second, accountability must be evaluated separately at political, operational and managerial levels. And third, at each level accountability is enacted by a system of several (partially) interdependent fora, forming together an accountability regime. The proposed framework is applied to the case of the German Bundesnetzagentur's accountability regime, which shows its suitability for empirical purposes. Regulatory agencies are often considered as independent, yet accountable. This article provides a realistic framework for the study of accountability 'regimes' in which they are embedded. It emphasizes the need to identify the various actors (accountability fora) to which agencies are formally accountable (parliamentary committees, auditing bodies, courts, and so on) and to consider possible relationships between them. It argues that formal accountability 'on paper', as defined in official documents, does not fully account for de facto accountability, which depends on the resources possessed by the fora (mainly information-processing and decision-making capacities) and the credibility of their sanctioning capacities. The article applies this framework to the German Bundesnetzagentur.

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Due to the existence of free software and pedagogical guides, the use of Data Envelopment Analysis (DEA) has been further democratized in recent years. Nowadays, it is quite usual for practitioners and decision makers with no or little knowledge in operational research to run their own efficiency analysis. Within DEA, several alternative models allow for an environmental adjustment. Four alternative models, each user-friendly and easily accessible to practitioners and decision makers, are performed using empirical data of 90 primary schools in the State of Geneva, Switzerland. Results show that the majority of alternative models deliver divergent results. From a political and a managerial standpoint, these diverging results could lead to potentially ineffective decisions. As no consensus emerges on the best model to use, practitioners and decision makers may be tempted to select the model that is right for them, in other words, the model that best reflects their own preferences. Further studies should investigate how an appropriate multi-criteria decision analysis method could help decision makers to select the right model.

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The main challenge for gaining biological insights from genetic associations is identifying which genes and pathways explain the associations. Here we present DEPICT, an integrative tool that employs predicted gene functions to systematically prioritize the most likely causal genes at associated loci, highlight enriched pathways and identify tissues/cell types where genes from associated loci are highly expressed. DEPICT is not limited to genes with established functions and prioritizes relevant gene sets for many phenotypes.

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Hotels and second home rentals are two of the most important tourist accommodation options in Spain. In terms of seasonality, almost all previous studies have analysed tourism demand from the point of view either of total arrivals or the number of tourists lodged in a single accommodation type (hotels, rural accommodation, etc). However, there are no studies focusing on price seasonality orcomparing seasonality among different accommodation types. By using seasonality indicators and a price index constructed by means of hedonic methods, this paper aims to shed some light on seasonal pricing patterns among second home rentals and hotels. The paper relies on a 2004 database of 144 hotels and 1,002 apartments on the Costa Brava (northeast Spain). The results show that prices for second home rentals display a smoother seasonal pattern than hotels due to reduced price differences between shoulder (May and October) and peak periods (August)

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It is usually argued that tourism exerts negative economic impacts in host jurisdictions through the increase in prices linked to increasing demand for basic services and goods from tourists. This paper surveys 149 products in 45 tourism and non-tourism jurisdictions in Catalonia (which represent a total of 18,500 prices) in order to test empirically several hypotheses related to differences in price levels in tourism and non-tourism jurisdictions. The main results show that prices in tourism jurisdictions are not significantly higher than those in non-tourism ones. The analysis suggests that tourists are likely to pay higher prices than natives for some products

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The thesis studies role based access control and its suitability in the enterprise environment. The aim is to research how extensively role based access control can be implemented in the case organization and how it support organization’s business and IT functions. This study points out the enterprise’s needs for access control, factors of access control in the enterprise environment and requirements for implementation and the benefits and challenges it brings along. To find the scope how extensively role based access control can be implemented into the case organization, firstly is examined the actual state of access control. Secondly is defined a rudimentary desired state (how things should be) and thirdly completed it by using the results of the implementation of role based access control application. The study results the role model for case organization unit, and the building blocks and the framework for the organization wide implementation. Ultimate value for organization is delivered by facilitating the normal operations of the organization whilst protecting its information assets.

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Recent advances in machine learning methods enable increasingly the automatic construction of various types of computer assisted methods that have been difficult or laborious to program by human experts. The tasks for which this kind of tools are needed arise in many areas, here especially in the fields of bioinformatics and natural language processing. The machine learning methods may not work satisfactorily if they are not appropriately tailored to the task in question. However, their learning performance can often be improved by taking advantage of deeper insight of the application domain or the learning problem at hand. This thesis considers developing kernel-based learning algorithms incorporating this kind of prior knowledge of the task in question in an advantageous way. Moreover, computationally efficient algorithms for training the learning machines for specific tasks are presented. In the context of kernel-based learning methods, the incorporation of prior knowledge is often done by designing appropriate kernel functions. Another well-known way is to develop cost functions that fit to the task under consideration. For disambiguation tasks in natural language, we develop kernel functions that take account of the positional information and the mutual similarities of words. It is shown that the use of this information significantly improves the disambiguation performance of the learning machine. Further, we design a new cost function that is better suitable for the task of information retrieval and for more general ranking problems than the cost functions designed for regression and classification. We also consider other applications of the kernel-based learning algorithms such as text categorization, and pattern recognition in differential display. We develop computationally efficient algorithms for training the considered learning machines with the proposed kernel functions. We also design a fast cross-validation algorithm for regularized least-squares type of learning algorithm. Further, an efficient version of the regularized least-squares algorithm that can be used together with the new cost function for preference learning and ranking tasks is proposed. In summary, we demonstrate that the incorporation of prior knowledge is possible and beneficial, and novel advanced kernels and cost functions can be used in algorithms efficiently.

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Problems related to fire hazard and fire management have become in recent decades one of the most relevant issues in the Wildland-Urban Interface (WUI), that is the area where human infrastructures meet or intermingle with natural vegetation. In this paper we develop a robust geospatial method for defining and mapping the WUI in the Alpine environment, where most interactions between infrastructures and wildland vegetation concern the fire ignition through human activities, whereas no significant threats exist for infrastructures due to contact with burning vegetation. We used the three Alpine Swiss cantons of Ticino, Valais and Grisons as the study area. The features representing anthropogenic infrastructures (urban or infrastructural components of the WUI) as well as forest cover related features (wildland component of the WUI) were selected from the Swiss Topographic Landscape Model (TLM3D). Georeferenced forest fire occurrences derived from the WSL Swissfire database were used to define suitable WUI interface distances. The Random Forest algorithm was applied to estimate the importance of predictor variables to fire ignition occurrence. This revealed that buildings and drivable roads are the most relevant anthropogenic components with respect to fire ignition. We consequently defined the combination of drivable roads and easily accessible (i.e. 100 m from the next drivable road) buildings as the WUI-relevant infrastructural component. For the definition of the interface (buffer) distance between WUI infrastructural and wildland components, we computed the empirical cumulative distribution functions (ECDF) of the percentage of ignition points (observed and simulated) arising at increasing distances from the selected infrastructures. The ECDF facilitates the calculation of both the distance at which a given percentage of ignition points occurred and, in turn, the amount of forest area covered at a given distance. Finally, we developed a GIS ModelBuilder routine to map the WUI for the selected buffer distance. The approach was found to be reproducible, robust (based on statistical analyses for evaluating parameters) and flexible (buffer distances depending on the targeted final area covered) so that fire managers may use it to detect WUI according to their specific priorities.

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This study investigates whether there are differences in profitability of PPI companies based on the growth strategy they have chosen to follow. It is examined whether those companies following organic growth strategy are more profitable than those companies following acquisitive growth strategy. It is also investigated are ones larger than the others, or are ones growing faster than the others. Also, the factors affecting the profitability of acquisitive companies are further examined. The results showed that there actually are differences between the two groups. Organically grown companies were found to be more profitable, smaller and growing slower than acquisitive companies. When it comes to examining only acquisitive companies there could be found factors that better or worsen the profitability of companies. For example targets that the company has bought in developing markets were making them more profitable.

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Tämän tutkimuksen tavoitteena oli ymmärtää, miten kohdeyrityksen työntekijöiden osaamisen johtaminen toteutuu. Tutkimus oli luonteeltaan kvalitatiivinen, ja sen empiirinen aineisto koostui kohdeyrityksen kahdeksan esimiehen teemahaastattelusta. Tulosten perusteella voidaan vahvistaa toiminnon osaamisen johtamisen ja osaamisen tunnistamisen toteutuneen toisen kehitysvaiheen mukaisesti. Esimiehet olivat ymmärtäneet työntekijöiden osaamisen merkityksen liiketoimintaa edistävänä tekijänä. Tärkeäksi kehittämisen kohteeksi nousi nykyinen kehityskeskustelukäytäntö, joka tulee muuttaa toiminnon liiketoimintaa ja työntekijöiden osaamista tukevampaan muotoon. Lisäksi esimiehillä oli työntekijöiden osaamisen johtamista varten käytössään erilaisia toimintatapoja ja työvälineitä, joita tulee jatkossa kehittää ja yhtenäistää.

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In this paper we examine whether airline prices on national routes are higher than those charged on international routes. Drawing on a database prepared specifically for this study, we estimate a pricing equation for all routes originating from Gran Canaria, Canary Islands, Spain; differentiating between national and international routes. A key difference between these two route types is that island residents benefit from discounts on domestic flights. When controlling for variables related to airline characteristics, market structure and demand, we find that national passengers who are non-residents on the islands are paying higher prices than international passengers.