Model-Free Prediction and Regression A Transformation-Based Approach to Inference /

• Main Author: Politis, Dimitris N. (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2015.
• Edition: 1st ed. 2015.
• Series: Frontiers in Probability and the Statistical Sciences
• Subjects: Statistics.; Statistical Theory and Methods.; Statistics and Computing/Statistics Programs.; Statistics for Business/Economics/Mathematical Finance/Insurance.

The Model-Free Prediction Principle expounded upon in this monograph is based on the simple notion of transforming a complex dataset to one that is easier to work with, e.g., i.i.d. or Gaussian. As such, it restores the emphasis on observable quantities, i.e., current and future data, as opposed to...

Table of Contents:

• Prediction: some heuristic notions
• The Model-free Prediction Principle
• Model-based prediction in regression
• Model-free prediction in regression
• Model-free vs. model-based confidence intervals
• Linear time series and optimal linear prediction
• Model-based prediction in autoregression
• Model-free inference for Markov processes
• Predictive inference for locally stationary time series
• Model-free vs. model-based volatility prediction.