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Co-authored-by: jose-donato <zmcdonato@gmail.com>
Co-authored-by: jose-donato <43375532+jose-donato@users.noreply.github.com>
Co-authored-by: andrewkenreich <andrew.kenreich@gmail.com>
2023-10-30 21:01:29 +00:00

4.0 KiB
Vendored

title, description, keywords
title description keywords
seasonalnaive This page provides detailed usage of the SeasonalNaive forecasting model including parameters definitions, examples, and results interpretation. It is meant as a guide for using SeasonalNaive to make economic predictions.
SeasonalNaive
Forecasting
Economic Predictions
Additive Seasonality
Multiplicative Seasonality
Models
Forecast Parameters
Time Series Analysis
Cross Validation Time Series
Statsforecast

import HeadTitle from '@site/src/components/General/HeadTitle.tsx';

Perform SeasonalNaive forecasting: https://nixtla.github.io/statsforecast/models.html#seasonalnaive

Usage

seasonalnaive [--naive] [-d {}] [-c TARGET_COLUMN] [-n N_DAYS] [-s {N,A,M}] [-p SEASONAL_PERIODS] [-w START_WINDOW] [--end S_END_DATE] [--start S_START_DATE] [--residuals] [--forecast-only] [--export-pred-raw]

Parameters

Name Description Default Optional Choices
naive Show the naive baseline for a model. False True None
target_dataset The name of the dataset you want to select None True None
target_column The name of the specific column you want to use close True None
n_days prediction days. 5 True None
seasonal Seasonality: N: None, A: Additive, M: Multiplicative. A True N, A, M
seasonal_periods Seasonal periods: 4: Quarterly, 7: Daily 7 True None
start_window Start point for rolling training and forecast window. 0.0-1.0 0.85 True None
s_end_date The end date (format YYYY-MM-DD) to select for testing None True None
s_start_date The start date (format YYYY-MM-DD) to select for testing None True None
residuals Show the residuals for the model. False True None
forecast_only Do not plot the historical data without forecasts. False True None
export_pred_raw Export predictions to a csv file. False True None

Examples

2022 Nov 07, 19:24 (🦋) /stocks/ $ forecast

2022 Nov 07, 19:24 (🦋) /forecast/ $ seasonalnaive AAPL

Cross Validation Time Series 1: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 115/115 [00:0200:00, 47.75it/s]
Forecast: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:0000:00, 14873.42it/s]
SeasonalNaive obtains MAPE: 4.26%


   Actual price: 138.38
┏━━━━━━━━━━━━┳━━━━━━━━━━━━┓
┃ Datetime   ┃ Prediction ┃
┡━━━━━━━━━━━━╇━━━━━━━━━━━━┩
│ 2022-11-07 │ 138.38     │
├────────────┼────────────┤
│ 2022-11-08 │ 144.80     │
├────────────┼────────────┤
│ 2022-11-09 │ 155.74     │
├────────────┼────────────┤
│ 2022-11-10 │ 153.34     │
├────────────┼────────────┤
│ 2022-11-11 │ 150.65     │
└────────────┴────────────┘