| Library: | times |
| See also: | armalik |
| Macro: | armacls | |
| Description: | estimates an autoregressive moving average process with mean zero by conditional least squares |
| Usage: | {y,wnv} = armacls(x,p,q) | |
| Input: | ||
| x | n-vector, the process | |
| p | scalar, the autoregression order | |
| q | scalar, the moving average order | |
| Output: | ||
| y | list containing 1. p+q-vector, the estimated parameters, 2. the number of iterations, and 3. a 0-1 scalar indicating convergence | |
| wnv | scalar, the estimate of the white noise variance | |
library("times")
randomize(0)
x = genarma(0.7,0.3,normal(500))
{y,wnv}=armacls(x,1,1)
y{1}
Contents of minimum [1,] 0.70623 [2,] 0.27249
| Library: | times |
| See also: | armalik |