Curve-Fit Objectives Functions
Objective functions used to fit decline models to production history.
6 functions
PO.Stats.SSE(observed, predicted)
Computes the sum of squared errors (SSE) between observed and predicted rate sequences. Returns a scalar value.
PO.Stats.WSSE(observed, predicted, weights)
Computes the weighted SSE between observed and predicted sequences.
PO.Stats.LogSSE(observed, predicted)
Computes the sum of squared errors (SSE) in log-space between observed and predicted rate sequences. Small positive epsilon added before taking logs to avoid log(0).
PO.Stats.WLogSSE(observed, predicted, weights)
Computes the weighted log-space SSE between observed and predicted sequences. Small positive epsilon added before taking logs to avoid log(0).
PO.Stats.RMSE(observed, predicted)
Computes the root mean squared error (RMSE) between observed and predicted sequences. RMSE = sqrt(SSE/n).
PO.Stats.R2(observed, predicted)
Computes the coefficient of determination (R²) between observed and predicted sequences. R² = 1 - SSE/TSS. Returns 1.0 for perfect fit.