Univariate Time Series Model
Mostrando 1-8 de 8 artigos, teses e dissertações.
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1. Predicting outcomes in partial nephrectomy: is the renal score useful?
ABSTRACT Introduction and Objective The R.E.N.A.L. nephrometry system (RNS) has been validated in multiple open, laparoscopic and robotic partial nephrectomy series. The aim of this study was to test the accuracy of R.E.N.A.L. nephrometry system in predicting perioperative outcomes in surgical treatment of kidney tumors <7.0cm in a prospective model. Mate
Int. braz j urol.. Publicado em: 2017-06
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2. Influence diagnostics in stochastic volatility models / Diagnostico de influencia em modelos de volatilidade estocastica
Model diagnostics is a key step to assess the quality of fitted models. In this sense, one of the most important tools is the analysis of influence. Peña (2005) introduced a way of assessing influence in linear regression models, which evaluates how each point is influenced by the others in the sample. This diagnostic strategy was adapted by Hotta and Motta
Publicado em: 2009
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3. Previsão da taxa de juros nominal no Brasil: uma avaliação comparativa entre curva de reação, modelos ARMA e VAR / An assessment of the performance of the central banks reaction function, ARMA and VAR models to forecast the nominal interest rate in Brazil
This work studies alternative econometric specifications potentially suitable for forecasting the nominal interest rate in Brazil. The group of evaluated models includes the Central Bank reaction function, a univariate time-series model and four different VAR specifications. The results show that the reaction function and the univariate time-series model pre
Publicado em: 2008
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4. STATE SPACE MODEL FOR TIME SERIES WITH BIVARIATE POISSON DISTRIBUTION: AN APPLICATION OF DURBIN-KOOPMAN METODOLOGY / MODELO EM ESPAÇO DE ESTADO PARA SÉRIES TEMPORAIS COM DISTRIBUIÇÃO POISSON BIVARIADA: UMA APLICAÇÃO DA METODOLOGIA DURBIN-KOOPMAN
In this thesis we consider a state space model for bivariate observations of count data. The approach used to solve the non analytical integrals that appears as the solution of the resulting non-Gaussian filter is a natural extension of the methodology advocated by Durbin and Koopman (DK). In our approach the aproximated Gaussian Model (AGM), has a diagonal
Publicado em: 2004
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5. REDES NEURAIS E REGRESSÃO DINÂMICA: UM MODELO HÍBRIDO PARA PREVISÃO DE CURTO PRAZO DA DEMANDA DE GASOLINA AUTOMOTIVA NO BRASIL / NEURAL NETWORK AND DYNAMIC REGRESSION: A HYBRID MODEL TO FORECAST THE SHORT TERM DEMAND OF PETROL IN BRAZIL
In this dissertation a short term model to forecast automotive gasoline demand in Brazil is proposed. From the methodology point of view, data is analyzed and a model using a bottom-up strategy is developed. In other words, a simple model is improved step by step until a proper model that sits well the reality is found. Departuring from a univariate model it
Publicado em: 2000
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6. ARTIFICIAL NEURAL NETWORKS IN TIME SERIES FORECASTING / REDES NEURAIS ARTIFICIAIS NA PREVISÃO DE SÉRIES TEMPORAIS
This dissertation investigates the use of Artificial Neural Nerworks (ANNs) in time series forecastig, especially financial time series, which are typically noisy and with no apparent periodicity. The dissertation covers four major parts: the study of Artificial Neural Networks and time series; the desing of ANNs applied to time series forecasting; the devel
Publicado em: 1994
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7. Ventricular outflow tract reconstructions with cryopreserved cardiac valve homografts. A single surgeon's 10-year experience.
OBJECTIVE: From January 1, 1985 through December 31, 1994, one surgeon implanted cryopreserved valved homografts into 149 patients--65 since December 1988. This latter series (II) was accomplished in a single hospital, facilitating patient follow-up with biannual echocardiograms. Analysis of these 65 patients is the primary focus of this report; the indicati
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8. Short-term significance of DNA ploidy and cell proliferation in breast carcinoma: a multivariate analysis of prognostic markers in a series of 308 patients.
AIM: To determine the importance of tumour DNA ploidy and cell proliferation, as measured by the S phase fraction (SPF), in relation to other established clinicopathological indicators of prognosis in breast cancer. METHODS: A prospective study of 308 patients. Tumours were staged following the TNM system criteria and were classified according to the histolo