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This topic has appeared in the trending rankings 1 time(s) in the past year. While it does not trend frequently, its appearance suggests a renewed or concentrated surge of public interest.
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In statistics the mean squared prediction error (MSPE), also known as mean squared error of the predictions, of a smoothing, curve fitting, or regression procedure is the expected value of the squared prediction errors (PE), the square difference between the fitted values implied by the predictive function and the values of the (unobservable) true value g. It is an inverse measure of the explanatory power of and can be used in the process of cross-validation of an estimated model.
Knowledge of g would be required in order to calculate the MSPE exactly; in practice, MSPE is estimated.
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Search interest data over the past 12 months indicates that this topic periodically attracts global attention. Sudden spikes often correlate with major news events, public statements, or geopolitical developments.