Evaluation of autoregressive time series prediction using validity of cross-validation

  • 5 years ago
Cross-Validation is a validation technique used to explain how well the estimated values from a fitted statistical model will generalize to the explanatory variables under study. The standard procedure for model validation is the K-fold CV as in Regression Analysis and classification problem. This blog discusses a note on the validity of Cross-Validation for evaluating autoregressive Time Series Prediction. Statswork offers statistical services as per the requirements of the customers. When you Order statistical Services at Statswork, we promise you the following – Always on Time, outstanding customer support, and High-quality Subject Matter Experts.
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