LQM Registry / forecasting
AR(1) Residual-Bootstrap Forecast
Seeded empirical residual bootstrap around an AR(1) process, producing distributional forecasts, quantile intervals and reproducible sample paths.
Model key
lq.forecasting.ar1-residual-bootstrapVersion1.0.0
Runtimepython-process
Model contract
Inputs are explicit.
{
"type": "object",
"required": [
"values"
],
"properties": {
"values": {
"type": "array",
"items": {
"type": "number"
},
"minItems": 20
}
}
}Output contract
Outputs are explicit.
{
"type": "object",
"required": [
"phi",
"distribution_forecast",
"interval_probability",
"scenarios",
"seeded_reproducibility"
]
}Default parameters
{
"horizon": 5,
"scenarios": 1000,
"interval": 0.90000000000000002220446049250313080847263336181640625,
"sample_paths": 8
}Example input
{
"values": [
100,
100.5,
100.900000000000005684341886080801486968994140625,
101,
101.599999999999994315658113919198513031005859375,
101.400000000000005684341886080801486968994140625,
102,
102.2000000000000028421709430404007434844970703125,
102.7999999999999971578290569595992565155029296875,
102.5,
103.099999999999994315658113919198513031005859375,
103.599999999999994315658113919198513031005859375,
103.400000000000005684341886080801486968994140625,
104,
104.5,
104.2000000000000028421709430404007434844970703125,
104.900000000000005684341886080801486968994140625,
105.099999999999994315658113919198513031005859375,
105.7000000000000028421709430404007434844970703125,
106,
105.7999999999999971578290569595992565155029296875,
106.400000000000005684341886080801486968994140625,
106.900000000000005684341886080801486968994140625,
107.099999999999994315658113919198513031005859375
]
}