Andere Kunden interessierten sich auch für
![BAYESIAN INFERENCE FOR STRUCTURAL CHANGES IN TIME SERIES MODELS]( "BAYESIAN INFERENCE FOR STRUCTURAL CHANGES IN TIME SERIES MODELS")
BAYESIAN INFERENCE FOR STRUCTURAL CHANGES IN TIME SERIES MODELS32,99 €![Time Series Forecasting Using Statistical And Neural Networks Models]( "Time Series Forecasting Using Statistical And Neural Networks Models")
Time Series Forecasting Using Statistical And Neural Networks Models32,99 €![Statistical Inference in Non-Linear Models in Econometrics]( "Statistical Inference in Non-Linear Models in Econometrics")
Statistical Inference in Non-Linear Models in Econometrics46,99 €![Statistical Inference in Autoregressive Models]( "Statistical Inference in Autoregressive Models")
Statistical Inference in Autoregressive Models53,99 €![Inference in General Statistical Models]( "Inference in General Statistical Models")
Inference in General Statistical Models46,99 €![Applications of UNI Variate Time Series Models and Neural Networks]( "Applications of UNI Variate Time Series Models and Neural Networks")
Applications of UNI Variate Time Series Models and Neural Networks40,99 €![Robust multivariate and nonlinear time series models]( "Robust multivariate and nonlinear time series models")
Robust multivariate and nonlinear time series models38,99 €
This book attempts to develope some new inferential procedures for time series regression models.An inferential method for a time series linear regression model with auto correlated disturbances using quarterly data, has been developed by proposing a test based on internally studentized residuals.Two modified estimation procedures have been proposed for time series regression models involving MA (1) and MA (q) process errors.Autoregressive moving averages and autoregressive conditionally heteroscadastic (ARCH) processesses have been specified systematically with their characteristics. The generalized ARCH model is specified and the effect of error structure on ARCH model has been explained. Two modified tests for detecting the problem of ARCH errors have been developed by using Box-pierce-lying test statistics based on internally studentized residuals. A new estimation procedure has been developed for ARCH model by using an interactive technique