Search Results - subject:"parameter estimation"

The Distance between Rival Nonstationary Fractional Processes

Robinson, Peter M - Suntory and Toyota International Centres for Economics … - 2004

Asymptotic inference on nonstationary fractional time series models, including cointegrated ones, is proceeding along two routes, determined by alternative definitions of nonstationary processes. We derive bounds for the mean squared error of the difference between (possibly tapered) discrete...

Persistent link: https://www.econbiz.de/10005670823

Measurement calibration/tuning & topology processing in power system state estimation

Abur, Ali (contributor) - 2003

State estimation plays an important role in modern power systems. The errors in the telemetered measurements and the connectivity information of the network will greatly contaminate the estimated system state. This dissertation provides solutions to suppress the influences of these errors. A...

Persistent link: https://www.econbiz.de/10009465166

Bootstrap Conditional Distribution Tests In the Presence of Dynamic Misspecification

Corradi, Valentina; Swanson, Norman R. - 2003

distribution tests when there is dynamic misspecification and parameter estimation error. Our approach differs from the literature … misspecification and parameter estimation error. In order to provide valid asymptotic critical values we suggest an extention of the … empirical process version of the block bootstrap to the case of non vanishing parameter estimation error. The findings from …

Persistent link: https://www.econbiz.de/10010263212

The Block Bootstrap for Parameter Estimation Error In Recursive Estimation Schemes, With Applications to Predictive Evaluation

Swanson, Norman R.; Corradi, Valentina - 2003

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Persistent link: https://www.econbiz.de/10010263214

Some Recent Developments in Predictive Accuracy Testing With Nested Models and (Generic) Nonlinear Alternatives

Corradi, Valentina; Swanson, Norman R. - 2003

constructing predictive accuracy tests, namely: the contribution of parameter estimation error, the choice of linear versus …

Persistent link: https://www.econbiz.de/10010263216

Bootstrap Specification Tests for Diffusion Processes

Corradi, Valentina; Swanson, Norman R. - 2003

that reflect data dependence and parameter estimation error (PEE). In order to obtain asymptotically valid critical values …

Persistent link: https://www.econbiz.de/10010263219

Maximin and Bayesian optimal designs for regression models

Dette, Holger; Haines, Linda M.; Imhof, Lorens A. - 2003

For many problems of statistical inference in regression modelling, the Fisher information matrix depends on certain nuisance parameters which are unknown and which enter the model nonlinearly. A common strategy to deal with this problem within the context of design is to construct maximin...

Persistent link: https://www.econbiz.de/10010306254

A note on maximin and Bayesian D-optimal designs in weighted polynomial regression

Biedermann, Stefanie; Dette, Holger - 2003

We consider the problem of finding D-optimal designs for estimating the coefficients in a weighted polynominal regression model with a certain efficiency function depending on two unknown parameters, which models he heteroscedastic error structure. This problem is tackled by adopting a Bayesian...

Persistent link: https://www.econbiz.de/10010306264

Local-global neural networks: a new approach for nonlinear time series modelling

Fariñas, Mayte Suarez; Pedreira, Carloe E.; Medeiros, … - 2003

In this paper, the Local Global Neural Networks model is proposed within the context of time series models. This formulation encompasses some already existing nonlinear models and also admits the Mixture of Experts approach. We place emphasis on the linear expert case and extensively discuss the...

Persistent link: https://www.econbiz.de/10011807298

Local-global neural networks: a new approach for nonlinear time series modelling

Farinãs, Mayte Suarez; Pedreira, Carlos Eduardo; … - Departamento de Economia, Pontifícia Universidade … - 2003

Persistent link: https://www.econbiz.de/10005534121