LQM Registry / evaluation
Prequential Forecast Evaluation
Online one-step-ahead evaluation of naive, AR(1) and linear-trend forecasters using only information available before each realized observation.
Model key
lq.evaluation.prequential-forecastVersion1.0.0
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": [
"evaluation_protocol",
"lookahead_guard",
"candidate_scores",
"selected_model",
"out_of_sample_observations"
]
}Default parameters
{
"initial_window": 12,
"recent_window": 10
}Example input
{
"values": [
100,
100.400000000000005684341886080801486968994140625,
100.7999999999999971578290569595992565155029296875,
101.2000000000000028421709430404007434844970703125,
101.7000000000000028421709430404007434844970703125,
102,
102.5,
102.900000000000005684341886080801486968994140625,
103.2999999999999971578290569595992565155029296875,
103.7999999999999971578290569595992565155029296875,
104.2000000000000028421709430404007434844970703125,
104.7000000000000028421709430404007434844970703125,
105.099999999999994315658113919198513031005859375,
105.599999999999994315658113919198513031005859375,
106,
106.400000000000005684341886080801486968994140625,
106.900000000000005684341886080801486968994140625,
107.2999999999999971578290569595992565155029296875,
107.7999999999999971578290569595992565155029296875,
108.2000000000000028421709430404007434844970703125,
108.7000000000000028421709430404007434844970703125,
109.099999999999994315658113919198513031005859375,
109.599999999999994315658113919198513031005859375,
110,
110.5,
110.900000000000005684341886080801486968994140625
]
}