# Consistent cross-validatory model-selection for dependent data: hv-block cross-validation

@article{Racine2000ConsistentCM, title={Consistent cross-validatory model-selection for dependent data: hv-block cross-validation}, author={Jeffrey S. Racine}, journal={Journal of Econometrics}, year={2000}, volume={99}, pages={39-61} }

## 169 Citations

Markov cross-validation for time series model evaluations

- Computer ScienceInf. Sci.
- 2017

Generalised correlated cross-validation

- Computer Science
- 2012

This work proposes an extension to GCV in the context of correlated errors, which is motivated by a natural definition for residual degrees of freedom and a potential maximum likelihood framework for Gaussian random processes.

Generalized Cross-Validation for Correlated Data ( GCV c )

- Computer Science

An extension to GCV is proposed in the context of correlated errors that has important implications about the definition for residual degrees of freedom, even in the independent case and a potential maximum likelihood framework.

On the usefulness of cross-validation for directional forecast evaluation

- Computer ScienceComput. Stat. Data Anal.
- 2014

Far Casting Cross-Validation

- Computer Science
- 2009

FCCV withholds correlated neighbors in every aspect of the cross-validation procedure and is a technique that stresses a fitted model’s ability to extrapolate rather than interpolate, which generally leads to better model selection in correlated datasets.

A Note on the Validity of Cross-Validation for Evaluating Time Series Prediction

- Computer Science
- 2015

It is shown that the particular setup in which time series forecasting is usually performed using Machine Learning methods renders the use of standard K-fold CV possible and empirically that K- fold CV performs favourably compared to both OOS evaluation and other time-series-specific techniques such as non-dependent cross-validation.

A comparison of machine learning model validation schemes for non-stationary time series data

- Computer Science
- 2019

A study design that perturbs global stationarity by introducing a slow evolution of the underlying data-generating process is introduced and the practical significance in a replication study of a statistical arbitrage problem is demonstrated.

A note on the validity of cross-validation for evaluating autoregressive time series prediction

- Computer ScienceComput. Stat. Data Anal.
- 2018

hv-Block Cross Validation is not a BIBD: a Note on the Paper by Jeff Racine (2000)

- Computer ScienceArXiv
- 2019

This note demonstrates that this is not the case, and thus the theoretical consistency of $hv$-block remains an open question, and provides a Python program counting the number of occurrences of each sample and each pair of samples.

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