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 ndarray when the model contains multiple components.

var_bounds: ndarray[tuple[int, int], dtype[float64]]¶

Array containing columns of lower and upper bounds