arch.univariate.ConstantVariance.compute_variance¶
- ConstantVariance.compute_variance(parameters: ndarray[tuple[int], dtype[float64]], resids: ndarray[tuple[int], dtype[float64]] | Series, sigma2: ndarray[tuple[int], dtype[float64]], backcast: float | ndarray[tuple[int], dtype[float64]], var_bounds: ndarray[tuple[int, int], dtype[float64]]) ndarray[tuple[int], dtype[float64]][source]¶
Compute the variance for the ARCH model.
- Parameters:¶
- parameters: ndarray[tuple[int], dtype[float64]]¶
Model parameters.
- resids: ndarray[tuple[int], dtype[float64]] | Series¶
Vector of mean zero residuals.
- sigma2: ndarray[tuple[int], dtype[float64]]¶
Array with same size as resids to store the conditional variance.
- backcast: float | ndarray[tuple[int], dtype[float64]]¶
Value to use when initializing ARCH recursion. Can be an array_like when the model contains multiple components.
- var_bounds: ndarray[tuple[int, int], dtype[float64]]¶
Array containing columns of lower and upper bounds.
- Returns:¶
sigma2 – The array of conditional variances, which is also modified in place.
- Return type:¶