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Springer Model-Free Prediction and Regression Monograph
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Description
Key Features
This Springer monograph presents a transformation-based approach to inference for prediction and regression tasks.
The Model-Free Prediction Principle focuses on transforming complex datasets into easier formats like Gaussian or i.i.d.
The text prioritizes observable quantities, including current and future data, instead of unobservable model parameters.
Users can find optimal predictors for various settings such as time series and regression analysis.
The Model-Free Bootstrap method enables the construction of frequentist prediction intervals for better data analysis.
Product Specifications
- Brand
- Springer
- Format
- hardcover
- ASIN
- 3319213466
- Domain
- Amazon UK
- Release Date
- 05 January 2016
- Listed Since
- 04 June 2015
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