Returns the confidence interval limits of the conditional mean forecast.
ARMA_FORECI(X, Order, mean, sigma, phi, theta, T, alpha, upper)
- is the univariate time series data (a one dimensional array of cells (e.g. rows or columns)).
- 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)
- is the model mean (i.e. mu).
- is the standard deviation of the model's residuals/innovations.
- are the parameters of the AR(p) component model (starting with the lowest lag).
- are the parameters of the MA(q) component model (starting with the lowest lag).
- is the forecast time/horizon (expressed in terms of steps beyond end of the time series).
- is the statistical significance level. If missing, a default of 5% is assumed.
- If true, returns the upper confidence interval limit. Otherwise, returns the lower limit.
upper description 0 return lower limit 1 return upper limit
ARMA_FORECI() function is deprecated as of version 1.63: use ARMA_FORE 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 number of parameters in the input argument - phi - determines the order of the AR component.
- The number of parameters in the input argument - theta - determines the order of the MA component.
|=ARMA_FORE($B$2:$B$30,1,$D$3,$D$4,$D$5,$D$6,1)||The conditional mean forecast value at T+1 (0.228)|
|=ARMA_FORECI($B$2:$B$30,1,$D$3,$D$4,$D$5,$D$6,1,5%,1)||Upper confidence interval limit for the forecasted conditional mean at T+1 (0.503)|
|=ARMA_FORECI($B$2:$B$30,1,$D$3,$D$4,$D$5,$D$6,1,5%,0)||Lower confidence interval limit for the forecasted conditional mean at T+1 (-0.046)|
- 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 Reisel; 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