arch.univariate.ConstantMean.fix

ConstantMean.fix(params: ndarray[tuple[int], dtype[float64]] | Series | Sequence[float], first_obs: int | str | datetime | datetime64 | Timestamp | None = None, last_obs: int | str | datetime | datetime64 | Timestamp | None = None) → ARCHModelFixedResult

Construct an ARCHModelFixedResult from fixed parameters.

Parameters:
params: ndarray[tuple[int], dtype[float64]] | Series | Sequence[float]

User specified parameters to use when generating the result. Must have the correct number of parameters for a given choice of mean model, volatility model and distribution, and be finite.

first_obs: int | str | datetime | datetime64 | Timestamp | None = None

First observation to use when fixing model. Dates, strings and periods can only be used with pandas inputs that have a DatetimeIndex or a PeriodIndex. An integer must be in [-nobs, nobs], and a date must be in the index. A negative integer counts from the end, as in a slice, so that first_obs=-100 uses the last 100 observations.

last_obs: int | str | datetime | datetime64 | Timestamp | None = None

Last observation to use when fixing model. An integer must be in [-nobs, nobs], and a date must be in the index. As in a slice, the observation at last_obs is not used, and a negative integer counts from the end, so that last_obs=-1 drops the last observation.

Returns:

results – Object containing model results.

Return type:

arch.univariate.base.ARCHModelFixedResult

Raises:

  • TypeError – If params cannot be converted to numbers, or first_obs or last_obs is not an integer or a date.

  • ValueError – If params does not have one element for each parameter of the model or contains NaN or inf, or first_obs or last_obs is outside the sample.

Notes

Parameters are not checked against model-specific constraints.