Model-Free One-Step-Ahead Prediction Intervals: Asymptotic Theory and Small Sample Simulations

One step ahead prediction using Fuzzy Boolean Neural Networks

Time series prediction is a problem with a wide range of applications, including energy systems planning, currency forecasting, stock exchange operations or traffic prediction. Accordingly, a number of different prediction approaches have been proposed such as linear models, Feedforward Neural network models, Recurrent Neural networks or Fuzzy Neural Models. In this paper one presents a predict...

One step ahead forecasting using

When dealing with time series the one step ahead forecasting problem based on experimental data is the problem of estimating the autoregression function of the underlying process When minimizing the expected forecast ing error is the main goal the exible approach has to be used to be able to adjust the complexity of the model to the complexity of the data Multilay ered perceptrons are a popular...

asymptotic property of order statistics and sample quntile

چکیده: فرض کنید که تابعی از اپسیلون یک مجموع نامتناهی از احتمالات موزون مربوط به مجموع های جزئی براساس یک دنباله از متغیرهای تصادفی مستقل و همتوزیع باشد، و همچنین فرض کنید توابعی مانند g و h وجود دارند که هرگاه امید ریاضی توان دوم x متناهی و امیدریاضی x صفر باشد، در این صورت می توان حد حاصلضرب این توابع را بصورت تابعی از امید ریاضی توان دوم x نوشت. حالت عکس نیز برقرار است. همچنین ما با استفاده...

Optimal one-step-ahead stochastic adaptive control

An optimal indirect stochastic adaptive control is obtained explicitly for linear time-varying discrete-time systems with general delay and white noise perturbation, while minimizing the variance of the output around a desired value one step ahead. The resulting controller incorporates parameter uncertainties. The solution unifies and generalizes previously known results, which become special c...

Small-Sample Model-Robust Confidence Intervals in Regression