Autoregressive Nonlinear Model
Mostrando 1-12 de 18 artigos, teses e dissertações.
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1. FITTING AND CALIBRATING A MIXED-EFFECTS SEGMENTED TAPER MODEL FOR BRUTIAN PINE
ABSTRACT Taper models are one of several necessary tools in modern forest inventory, giving information on diameter at any point along the tree stem and this information can also be used to estimate stem volume. In this study, we used nonlinear mixed-effects (NLME) modeling approach to minimize existing statistical problems in constructing taper equations. A
CERNE. Publicado em: 2020-12
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2. Estimação e previsão da estrutura a termo das taxas de juros usando técnicas de inteligência computacional / Term structure of interest rate modeling and forecasting using computational intelligence techniques
This work proposes the term structure of interest rates modeling and forecasting using computational intelligence techniques, based on data from the US and Brazilian fixed income markets. The yield curve modeling includes the use of some evolutionary computation methods like Genetic Algorithms, Differential Evolution and Evolution Strategies in comparison wi
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 25/06/2012
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3. Transformações em modelos de séries temporais / Transformations in time series models
Cordeiro and Andrade (2009) incorporate the idea of transforming the response variable to the GARMA model, generalized autoregressive moving average, introduced by Benjamin et al. (2003), thus developing the TGARMA model, transformed generalized autoregressive moving average. The goal of this thesis is to develop the TGARMA model introduced by Cordeiro and A
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 21/05/2012
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4. Estimação indireta de modelos R-GARCH / Indirect inference of R-GARCH models
Linear processes do not capture the structure of financial data. There is a large variety of nonlinear models available in literature. The class of ARCH models (Autoregressive Conditional Heterokedastic) was introduced by Engle (1982) in order to estimate inflation\ s variance. The idea is that, in this class, returns are serially uncorrelated, but the volat
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 01/03/2012
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5. Determinantes da taxa de juros no Brasil: uma abordagem não-linear
This paper investigates the interest rate determination in Brazil based on autoregressive Markov-Switching Process (MS-VAR). Initially developed to model US business cycle, the MS-VAR approach has been used in several fields in conomics due to its flexibility and to its important empirical results, based on estimates of nonlinear parameters of the regression
Publicado em: 2010
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6. Convergence clubs in income in America: an approach through non-linear dynamic panel with variable threshold / Clubes de convergÃncia de renda na AmÃrica: uma abordagem atravÃs de painel dinÃmico nÃo-linear com variÃvel limiar
The main objectives of this work are to test empirically the hypothesis of income convergence process among American countries, to classify this convergence process as either absolute or conditional and to determine if this process happens in either a linear or non-linear manner. Estimations were made through both TAR (threshold autoregressive) panel and lin
IBICT - Instituto Brasileiro de Informação em Ciência e Tecnologia. Publicado em: 07/05/2009
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7. Avaliação de controle neural a um processo de quatro tanques acoplados
The main goal of this doctorate thesis is the evaluation of neural control on a four interconnected tanks process, in laboratory environment, where the controlled variable is the water level height of the fourth tank. The dynamics of this process is non linear, as the outflow from the tanks depends on the square root of corresponding water height. This type
Publicado em: 2009
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8. Curvas de crescimento difÃsicas de fÃmeas Hereford com erros auto-regressivos e heterogeneidade de variÃncias / Difasic growth curves of Hereford females with auto-regressive errors and heterogenety of variances.
In the present study, the models of non-linear Difasic Logistic and Difasic Gompertz were adjusted, both weighed by the inverse of the variance with three different errors structures: independent errors (IE), first-class auto-regressive (AR (1)) and second-class auto-regressive (AR (2)) to weight-age data of 55 females of the Hereford race, raised in the Bag
Publicado em: 2007
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9. HIGH FREQUENCY DATA AND PRICE-MAKING PROCESS ANALYSIS: THE EXPONENTIAL MULTIVARIATE AUTOREGRESSIVE CONDITIONAL MODEL - EMACM / ANÁLISE DE DADOS DE ALTA FREQÜÊNCIA E DO PROCESSO DE FORMAÇÃO DE PREÇOS: O MODELO MULTIVARIADO EXPONENCIAL - EMACM
The availability of high frequency financial transaction data - price, spread, volume and duration -has contributed to the growing number of scientific articles on this topic. The first proposals were limited to pure duration models. Later, the impact of duration over instantaneous volatility was analyzed. More recently, Manganelli (2002) included volume int
Publicado em: 2006
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10. Construção de um índice de cointegração e utilização do modelo de regimes Markovianos de conversão para a identificação de risco e retorno: evidência a partir de ações na Bolsa de Valores de São Paulo
One of the most popular subjects in finance is about the search and the learning of the securities return generation process and originate with the publication of Bacheliers thesis, in 1900. In 1978, Jensen affirmed that, any strategy of business, that produces economic profits in a consistent way, discounted the risk, for a sufficient long period, observing
Publicado em: 2006
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11. Modelos de prediÃÃo linear para anÃlise de sinais eletroencefalogrÃficos (EEG) e de matrizes multieletrodo (MEA) / Linear-prediction models for electroencephalographic (EEG) and multielectrode-array (MEA) signal analysis
This work establishes models of neurophysiological signals, which are composed of spontaneous activity measurements taken by means of multielectrode arrays (MEAs) applied on in vitro cell cultures; as well as of neurological signals based on electroencephalography. These models suppose that MEAs are employed as neuroprostheses applied for detection and forec
Publicado em: 2006
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12. Identificação de sistemas "on-line", otimização e controle avançado com o filtro de Kalman estendido / On line system identification, advanced control and optimization with the (Extended) Kalman filter
In the continuing competition between it will be more and more necessary to optimize current chemical processes in real time. To be able to optimize a plant in real time, there have to be various aspects to be fulfilled, such as measurement, reliability of the measurement and prediction of the process behaviour. In this work some of the aspects of such an ad
Publicado em: 2006