identify_cross
Detect residual cross-correlations between time series pairs to reveal dynamic links and return candidate cross orders and contemporaneous covariance terms for VARMA identification.
Instructions
N2 — What the univariate models do NOT carry: residual cross-correlations.
Reads the CCFs of the residuals of the diagonal system, pair by pair. Those residuals are each series' own innovations — prewhitened by construction — so a cross-correlation beyond the band is evidence of a dynamic between the series. Contemporaneous correlation points to a full innovation covariance; lead-lag correlation points to cross orders p (and q). Returns the evidence and the menu of candidates, each with its argument. It does not choose.
nlags defaults to twice the frequency (24 for monthly data).
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_cross"
}
}Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| nlags | No |
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |