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Forecasting the classic AirPassengers time series with ETS, ARIMA, NNAR and Prophet. Includes full R code, hold-out metrics and practical recommendations.

This analytic tool provides a GLS-based within-study meta-analytic method to combine multiple correlation coefficients from a single study—accounting for the statistical dependency between them to produce a single pooled correlation estimate. It uses the generalized least squares (GLS) framework, weighting each correlation by its precision and accounting for their inter-correlations via a covariance matrix.