We develop a new targeted maximum likelihood estimation method that provides improved forecasting for misspecified linear autoregressive models. The method weighs data points in the observed sample and is useful in the presence of data generating processes featuring structural breaks, complex...

Rainfall is one of the fundamental components of the hydrological cycle as its accurate estimation is necessary for planning, designing and operation of water resources development programmes. In the present study, monthly stochastic model was developed using rainfall data for Doimukh...

The state-space method is applied to the problem of separating an autoregressive (AR) signal from composite AR and white normal noise. In the stationary case, for which the Wiener filter exists, we show explicitly its equavalence to the steady-state Kalman filter. Existing results for...

Comparative analysis of economic structure and forecasts generated from simultaneous equation, VAR and autoregressive models based on quarterly series from 1966:1 to 2007:3 of UK to those from the stochastic general equilibrium models has provided insights into objective and subjective...