Computes the maximum likelihood estimate (MLE) of the model's parameters.
ARMA_CALIBRATE ([x], order, µ, σ, [φ], [θ], maxiter)
- Required. Is the univariate time series data (a one-dimensional array of cells (e.g., rows or columns)).
- Optional. Is the time order in the data series (i.e., the first data point's corresponding date (earliest date = 1 (default), latest date = 0)).
Value Order 1 Ascending (the first data point corresponds to the earliest date) (default). 0 Descending (the first data point corresponds to the latest date).
- Optional. Is the ARMA model long-run mean (i.e., mu). If missing, the process mean is assumed to be zero.
- Required. Is the standard deviation value of the model's residuals/innovations.
- Optional. Are the parameters of the AR(p) component model: [φ1, φ2 … φp] (starting with the lowest lag).
- Optional. Are the parameters of the MA(q) component model: [θ1, θ2 … θq] (starting with the lowest lag).
- Optional. Is the maximum number of iterations used to calibrate the model. If missing, the default maximum of 100 is assumed.
ARMA_CALIBRATE(.) function is deprecated as of version 1.63: use ARMA_PARAM(.) function instead.
- The underlying model is described here.
- The time series is homogeneous or equally spaced.
- The time series may include missing values (e.g., #N/A) at either end.
- The Maximum Likelihood Estimation (MLE) is a statistical method for fitting a model to the data and provides estimates for the model's parameters.
- D. S.G. Pollock; Handbook of Time Series Analysis, Signal Processing, and Dynamics; Academic Press; Har/Cdr edition(Nov 17, 1999), ISBN: 125609906.
- James Douglas Hamilton; Time Series Analysis, Princeton University Press; 1st edition(Jan 11, 1994), ISBN: 691042896.
- Tsay, Ruey S.; Analysis of Financial Time Series, John Wiley & SONS; 2nd edition(Aug 30, 2005), ISBN: 0-471-690740.
- Box, Jenkins and Reinsel; Time Series Analysis: Forecasting and Control; John Wiley & SONS.; 4th edition(Jun 30, 2008), ISBN: 470272848.
- Walter Enders; Applied Econometric Time Series; Wiley; 4th edition(Nov 03, 2014), ISBN: 1118808568.