1000 resultados para Minification models
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Forecasting future sales is one of the most important issues that is beyond all strategic and planning decisions in effective operations of retail businesses. For profitable retail businesses, accurate demand forecasting is crucial in organizing and planning production, purchasing, transportation and labor force. Retail sales series belong to a special type of time series that typically contain trend and seasonal patterns, presenting challenges in developing effective forecasting models. This work compares the forecasting performance of state space models and ARIMA models. The forecasting performance is demonstrated through a case study of retail sales of five different categories of women footwear: Boots, Booties, Flats, Sandals and Shoes. On both methodologies the model with the minimum value of Akaike's Information Criteria for the in-sample period was selected from all admissible models for further evaluation in the out-of-sample. Both one-step and multiple-step forecasts were produced. The results show that when an automatic algorithm the overall out-of-sample forecasting performance of state space and ARIMA models evaluated via RMSE, MAE and MAPE is quite similar on both one-step and multi-step forecasts. We also conclude that state space and ARIMA produce coverage probabilities that are close to the nominal rates for both one-step and multi-step forecasts.
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Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Engenharia Electrotécnica e Computadores
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Leishmaniasis remains a major public health problem worldwide and is classified as Category I by the TDR/WHO, mainly due to the absence of control. Many experimental models like rodents, dogs and monkeys have been developed, each with specific features, in order to characterize the immune response to Leishmania species, but none reproduces the pathology observed in human disease. Conflicting data may arise in part because different parasite strains or species are being examined, different tissue targets (mice footpad, ear, or base of tail) are being infected, and different numbers (“low” 1×102 and “high” 1×106) of metacyclic promastigotes have been inoculated. Recently, new approaches have been proposed to provide more meaningful data regarding the host response and pathogenesis that parallels human disease. The use of sand fly saliva and low numbers of parasites in experimental infections has led to mimic natural transmission and find new molecules and immune mechanisms which should be considered when designing vaccines and control strategies. Moreover, the use of wild rodents as experimental models has been proposed as a good alternative for studying the host-pathogen relationships and for testing candidate vaccines. To date, using natural reservoirs to study Leishmania infection has been challenging because immunologic reagents for use in wild rodents are lacking. This review discusses the principal immunological findings against Leishmania infection in different animal models highlighting the importance of using experimental conditions similar to natural transmission and reservoir species as experimental models to study the immunopathology of the disease.
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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.
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Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica
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Dissertation to obtain master degree in Genética Molecular e Biomedicina
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ABSTRACT: Financing is a critical factor in ensuring the optimal development and delivery of a mental health system. The primary method of financing worldwide is tax-based. However many low income countries depend on out-of-pocket payments. There is a report on Irish Health Care funding but none that deals exclusively with mental health care. This paper analyses the various financial models that exist globally with respect to financing the mental health sector, examines the impact of various models on service users, especially in terms of relative ‘financial burden’ and provides a more detailed examination of the current mental health funding situation in Ireland After extensive internet and hardcopy research on the above topics, the findings were analysed and a number of recommendations were reached. Mental health service should be free at the point of delivery to achieve universal coverage. Government tax-based funding or mandatory social insurance with government top-ups, as required, appears the optimal option, although there is no one funding system applicable everywhere. Out-of-pocket funding can create a crippling financial burden for service users. It is important to employ improved revenue collection systems, eliminate waste, provide equitable resource distribution, ring fence mental health funding and cap the number of visits, where necessary. Political, economic, social and cultural factors play a role in funding decisions and this can be clearly seen in the context of the current economic recession in Ireland. Only 33% of the Irish population has access to free public health care and the number health insurance policy holders has dramatically declined, resulting in increased out-of-pocket payments. This approach risks negatively impacting on the social determinants of health, increasing health inequalities and negatively affecting economic productivity. It is therefore important the Irish government examines other options to provide funding for mental health services.
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Dissertação para obtenção do Grau de Doutor em Engenharia Mecânica
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Dissertação para obtenção do Grau de Doutor em Engenharia Informática
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economics
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We would like to thank Philipp Schwarz and Julia Gückel for their dedicated support in preparing this paper and our colleagues and students of the School of Engineering and the Business School for our fruitful discussions.
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Dissertation to obtain master degree in Biotechnology
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The continued increase in availability of economic data in recent years and, more importantly, the possibility to construct larger frequency time series, have fostered the use (and development) of statistical and econometric techniques to treat them more accurately. This paper presents an exposition of structural time series models by which a time series can be decomposed as the sum of a trend, seasonal and irregular components. In addition to a detailled analysis of univariate speci fications we also address the SUTSE multivariate case and the issue of cointegration. Finally, the recursive estimation and smoothing by means of the Kalman filter algorithm is described taking into account its different stages, from initialisation to parameter s estimation.
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A Masters Thesis, presented as part of the requirements for the award of a Research Masters Degree in Economics from NOVA – School of Business and Economics