LQM Registry / time-series
AR(1) Time-Series Forecast
Autoregressive AR(1) estimation and recursive forecasting with residual uncertainty propagation and stationarity diagnostics.
Model key
lq.timeseries.ar1Version1.0.0
Runtimepython-process
Model contract
Inputs are explicit.
{
"type": "object",
"required": [
"values"
],
"properties": {
"values": {
"type": "array",
"items": {
"type": "number"
},
"minItems": 8
}
}
}Output contract
Outputs are explicit.
{
"type": "object",
"required": [
"phi",
"intercept",
"stationary",
"forecast",
"intervals",
"rmse"
]
}Default parameters
{
"horizon": 5,
"interval_z": 1.95996398454005404943245594040490686893463134765625
}Example input
{
"values": [
100,
100.7999999999999971578290569595992565155029296875,
101.099999999999994315658113919198513031005859375,
102,
102.400000000000005684341886080801486968994140625,
103.2000000000000028421709430404007434844970703125,
103,
104.099999999999994315658113919198513031005859375,
104.7999999999999971578290569595992565155029296875,
105.2000000000000028421709430404007434844970703125,
105.900000000000005684341886080801486968994140625,
106.400000000000005684341886080801486968994140625
]
}