identify_matrices
Identifies AR and MA orders for multiple time series by computing prewhitened residual, partial, and Alavi q-conditioned correlation matrices, then comparing results with specification warnings.
Instructions
N2 — Jenkins and Alavi's (1981) two identifications, as matrices.
Method 2, prewhitened: the correlation matrices R_k of the residuals of the
diagonal system (the univariate models' residuals), which suggest an MA
residual model and its links. Method 1, not prewhitened: R_k, the partial
correlation matrices S_k (multivariate Yule-Walker) and Alavi's
q-conditioned S_k(q) of the stationary series of the same files, which
suggest the AR (and ARMA) orders; determinants with three or more series.
Then the comparison as a menu, with their warning when a cross AR shows:
prewhitening can mis-specify it. nlags defaults to max(6, frequency);
qmax the largest q-conditioning. Complements identify_cross (the
pairwise CCFs).
Tool call template
Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {
"name": "<name>"
},
"name": "identify_matrices"
}
}Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| qmax | No | ||
| nlags | No |
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |