Made available in DSpace on 2016-08-17T14:53:03Z (GMT). No. of bitstreams: 1 Jorge Farid Amate.pdf: 1076998 bytes, checksum: 7c54d6bc2833288f1945368aa6976936 (MD5) Previous issue date: 2009-02-06 / Conselho Nacional de Desenvolvimento Científico e Tecnológico / In industrial processes, where parameters estimation and standard recognition are desired, digital filters technology is used to do estimation. The digital filter is responsible for prediction and filtering process. Then, the filter behavior can be analyzed based on performance, gains and others variables linked to the specified model. However, to obtain trusty variables and data to estimate the process in question, a model that represents well the physics plant is needed. To do this, are applied techniques based on Systems Identification where we obtain the ARX, ARMAX, Output-Error and Box-Jenkins models of the electrolytic pot. Results, validation and their analysis, applied in standard recognition, using different structures are presented. / Em processos industriais, onde deseja-se a estimação de parâmetros e reconhecimento de padrões, utiliza-se da tecnologia de filtros digitais para tal fim. O filtro digital é responsável pelo processo de predição e filtragem. Assim, pode-se fazer uma análise do comportamento do filtro baseada no desempenho, ganhos e outras variáveis ligadas ao modelo especificado. Porém, para obtenção de variáveis e dados confiáveis para estimar-se o processo em questão, necessita-se de um modelo que represente bem a planta física. Para isto, são aplicadas técnicas baseadas em Identificação de Sistemas, onde são obtidos os modelos ARX, ARMAX, Output-Error e Box-Jenkins da cuba eletrolítica. São apresentados os resultados, validações dos modelos e análise dos mesmos, aplicados ao reconhecimento de padrões, utilizando-se diferentes estruturas.

Mise en oeuvre de techniques de modélisation récentes pour la prévision statistique et économique. / Doctorat en Sciences / info:eu-repo/semantics/nonPublished

This thesis aims to provide an approach to real estate residential modeling and forecasting covering property types’ correlation, time series attributes within a region or a city, and socio-economic attributes of preferred real estate locations. The thesis covers residential estate markets and concentrates on property types, while previous studies that have considered country wide house price indices. There is a gap identified in the literature in the need to study correlations between property types within a region or a city and whether they will provide diversification benefits for real estate investors such as risk reduction per unit of returns. The thesis concentrates on property type seasonality in addition to modeling time series attributes within a region or city instead of real estate index seasonality. This thesis the first to combine modern information systems techniques such as geographic information systems (GIS) with socio-economic factors to help understanding causal relationships that can be used to forecast real estate prices. The results show that it is more achievable to forecast real estate prices within a city than for the real estate market of the entire country. The GIS and socio-economic modeling results show that higher property prices are awarded to real estate with more green spaces, residents with higher disposable incomes, lower council tax bands, fewer tax benefits claimants, and better health services. Previous studies have examined real estate price indices at the macro level (the general, all real estate house price indices). There has not been a study that examines real estate price forecasts by property types within a city. The contribution of this thesis is its focus on time series analysis as well as causal modeling within a city with the objective of providing a better understanding of the dynamics of real estate price changes.

In this work we will describe methods for modeling multivariate financial time series. We will concentrate on both modeling expected value by multi- variate Box-Jenkins processes and primarily on modeling conditional corre- lations and volatility. Our main object will be DCC (Dynamic Conditional Correlation) model, estimation of its parameters and some other general- izations. Then we will programme DCC model in statistical software R and apply on real data. In applications we will concentrate on problem of high dimension of financial time series and on modeling conditional correlations data with outliers.

Title: Influence of errors to regression model Author: Bc. Vlasta Poliačková Department: Department of Probability and Mathematical Statistics Supervisor: doc. RNDr. Petr Lachout, CSc. Supervisor's e-mail address: Petr.Lachout@mff.cuni.cz Abstract: The submitted work deals with the regression model, and the influence of errors to regression. Thesis describes different types of violations of assumptions re- quired to the error term and their impact to the properties of the regression model. In the next part, there are discussed various statistical approaches applicable in the case of violation assumptions of regression model such as heteroscedasticity or autocor- relation of the residuals. In the application part, there is used mainly knowledge of Box - Jenkins methodology. In this section it is described in detail how to build a Box - Jenkins models and forecasts of future values for various real financial time series. In processing of the data are used models of ARMA, ARIMA and SARIMA. In an example, forecasts of the models are compared to real future values of the time series. Keywords: regression, violation of assumptions, error term, Box-Jenkins methodo- logy, time series

Dissertação (mestrado) - Pontifícia Universidade Católica do Paraná, Curitiba, 2010 / Bibliografia: p.99-109 / O panorama atual da economia globalizada mostra que o ambiente organizacional está muito competitivo e dinâmico. Os mecanismos e os aspectos de como as organizações desenvolvem, planejam e implementam uma estratégia organizacional podem representar ganhos / The current scenario of the globalized economy shows that the organizational environment is very competitive and dynamic. The mechanisms and aspects of how organizations develop, plan and implement an organizational strategy may represent gains or losses.

This thesis deals about using models of neural networks like alternative of time series model based on Box-Jenkins methodology. The work is divided into two parts according to the model construction method. Each of the parts contains a theory that explains the individual processes and the progress of the model construction. This is followed by two experiments demonstrating the difference in approach to the design of a given model and creating a forecast by estimated values. for the following year. The last part expertly evaluates the quality of the predictions and considers the use of neural networks against prediction models as an alternative to Box-Jenkins methodology based models

This work concerns the creation of automatized procedure of ARIMA and SARIMA class model choice according to Box-Jenkins methodology and in this connection, also deals with force testing of unit roots and analysis of applying of informatics criteria when choosing a model. The goal of this work is to create an application in the environment R that can automatically choose a model of time array generating process. The procedure is verified by a simulation study. In this work an effect of values of generating ARMA (1,1) model processes parameters is examined, for his choice and power of KPSS test, augmented Dickey-Fuller and Phillips-Peron test of unit roots.

V této diplomové práci se zaměřujeme na vytvoření plně automatizovaného algoritmu pro předpovědi finančních řad, který se snaží využít kombinační proceduru na dvou úrovních mezi dvěma rodinami předpovědních modelů, Box-Jenkins a Exponenciální stavové modely, které jsou schopny modelovat jak homoskedastické tak heteroskedastické časové řady. Pro tento účel jsme navrhli selekční proceduru v prostředí MATLAB pro modely ARIMA. Výsledný kombinovaný model je pak aplikován několik finančních časových řad a jeho výkonost je diskutována.

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.