Returns an array of cells for the quick guess, optimal (calibrated) or std. errors of the values of model's parameters.
Syntax
SARIMA_PARAM(X, Order, mean, sigma, d, phi, theta, period, sd, sPhi, sTheta, Type, maxIter)
- X
- is the univariate time series data (a one dimensional array of cells (e.g. rows or columns)).
- Order
- is the time order in the data series (i.e. the first data point's corresponding date (earliest date=1 (default), latest date=0)).
Order Description 1 ascending (the first data point corresponds to the earliest date) (default) 0 descending (the first data point corresponds to the latest date) - mean
- is the ARMA model mean (i.e. mu). If missing, mean is assumed zero.
- sigma
- is the standard deviation value of the model's residuals/innovations.
- d
- is the non-seasonal difference order.
- phi
- are the parameters of the non-seasonal AR model component AR(p) (starting with the lowest lag).
- theta
- are the parameters of the non-seasonal MA model component (i.e. MA(q)) (starting with the lowest lag).
- period
- is the number of observations per one period (e.g. 12=Annual, 4=Quarter).
- sd
- is the seasonal difference order.
- sPhi
- are the parameters of the seasonal AR model component AR(p) (starting with the lowest lag).
- sTheta
- are the parameters of the seasonal MA model component (i.e. MA(q)) (starting with the lowest lag).
- Type
- is an integer switch to select the output array: (1=Quick Guess (default), 2= Calibrated , 3=Std. Errors).
Order Description 1 Quick guess (non-optimal) of parameters values (default) 2 Calibrated (optimal) values for the model's parameters 3 Standard error of the parameters' values - maxIter
- is the maximum number of iterations used to calibrate the model. If missing, the default maximum of 100 is assumed.
Remarks
- 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.
- SARIMA_PARAM returns an array for the values (or errors) of the model's parameters in the following order:
- $\mu$
- $\phi_1,\phi_2,...,\phi_p$
- $\theta_1,\theta_2,...,\theta_q$
- $\Phi_1,\phi_2,...,\phi_P$
- $\Theta_1,\theta_2,...,\theta_Q$
- $\sigma$
- The long-run mean argument (mean) can take any value or be omitted, in which case a zero value is assumed.
- The residuals/innovations standard deviation (sigma) must be greater than zero.
- For the input argument - phi (parameters of the non-seasonal AR component):
- The input argument is optional and can be omitted, in which case no non-seasonal AR component is included.
- The order of the parameters starts with the lowest lag.
- One or more parameters may have missing values or error codes (i.e. #NUM!, #VALUE!, etc.).
- The order of the non-seasonal AR component model is solely determined by the order of the last value in the array with a numeric value (vs. missing or error).
- For the input argument - theta (parameters of the non-seasonal MA component):
- The input argument is optional and can be omitted, in which case no non-seasonal MA component is included.
- The order of the parameters starts with the lowest lag.
- One or more values in the input argument can be missing or an error code (i.e. #NUM!, #VALUE!, etc.).
- The order of the non-seasonal MA component model is solely determined by the order of the last value in the array with a numeric value (vs. missing or error).
- For the input argument - sPhi (parameters of the seasonal AR component):
- The input argument is optional and can be omitted, in which case no seasonal AR component is included.
- The order of the parameters starts with the lowest lag.
- One or more parameters may have missing values or error codes (i.e. #NUM!, #VALUE!, etc.).
- The order of the seasonal AR component model is solely determined by the order of the last value in the array with a numeric value (vs. missing or error).
- For the input argument - sTheta (parameters of the seasonal MA component):
- The input argument is optional and can be omitted, in which case no seasonal MA component is included.
- The order of the parameters starts with the lowest lag.
- One or more values in the input argument can be missing or an error code (i.e. #NUM!, #VALUE!, etc.).
- The order of the seasonal MA component model is solely determined by the order of the last value in the array with a numeric value (vs. missing or error).
- The non-seasonal integration order - d - is optional and can be omitted, in which case d is assumed to be zero.
- The seasonal integration order - sD - is optional and can be omitted, in which case sD is assumed to be zero.
- The season length - s - is optional and can be omitted, in which case s is assumed to be zero (i.e. plain ARIMA).
- The function was added in version 1.63 SHAMROCK.
Files Examples
Related Links
References
- Hamilton, J .D.; Time Series Analysis , Princeton University Press (1994), ISBN 0-691-04289-6
- Tsay, Ruey S.; Analysis of Financial Time Series John Wiley & SONS. (2005), ISBN 0-471-690740
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