Old docs #25
Draft
Old docs #25
Mintlify / Mintlify Deployment
succeeded
Dec 22, 2025 in 34s
Deployment Succeeded
Your changes are now live at https://nixtlaverse.nixtla.io!
Details
Verified update permissions
Fetching and validating config file...
Successfully validated docs.json
Fetching .mintignore file...
No .mintignore file found
Fetched all file paths
Fetched 0 OpenApi file(s)
Fetched 0 AsyncApi file(s)
Skipped OpenAPI navigation generation
Skipped AsyncAPI navigation generation
Successfully updated API reference metadata.
No stale files found
Updating targeted paths:
neuralforecast/models.rnn.html.mdx
Successfully updated deployment
LaTeX configuring is unchanged
Successfully saved config
No stale tracked assets found
Updating navigation...
Navigation updated
Beginning search indexing...
Successfully indexed 1 page(s).
Successfully deleted stale OpenAPI document(s)
Successfully deleted stale AsyncAPI document(s)
Cached valid paths
Starting page revalidation...
Revalidating all pages...
Revalidating paths:
coreforecast/differences
coreforecast/expanding
coreforecast/exponentially_weighted
coreforecast/grouped_array
coreforecast/index
coreforecast/lag_transforms
coreforecast/rolling
coreforecast/scalers
coreforecast/seasonal
coreforecast/utils
datasetsforecast/favorita.html
datasetsforecast/hierarchical.html
datasetsforecast/index.html
datasetsforecast/long_horizon.html
datasetsforecast/long_horizon2.html
datasetsforecast/m3.html
datasetsforecast/m4.html
datasetsforecast/m5.html
datasetsforecast/phm2008.html
datasetsforecast/utils.html
hierarchicalforecast/examples/australiandomestictourism-bootstraped-intervals.html
hierarchicalforecast/examples/australiandomestictourism-intervals.html
hierarchicalforecast/examples/australiandomestictourism-multimodel.html
hierarchicalforecast/examples/australiandomestictourism-permbu-intervals.html
hierarchicalforecast/examples/australiandomestictourism.html
hierarchicalforecast/examples/australiandomestictourismcrosstemporal.html
hierarchicalforecast/examples/australiandomestictourismtemporal.html
hierarchicalforecast/examples/australianprisonpopulation.html
hierarchicalforecast/examples/index
hierarchicalforecast/examples/installation.html
hierarchicalforecast/examples/introduction.html
hierarchicalforecast/examples/localglobalaggregation.html
hierarchicalforecast/examples/m3withthief.html
hierarchicalforecast/examples/mlframeworksexample.html
hierarchicalforecast/examples/nonnegativereconciliation.html
hierarchicalforecast/examples/tourismlarge-evaluation.html
hierarchicalforecast/examples/tourismsmall.html
hierarchicalforecast/examples/tourismsmallpolars.html
hierarchicalforecast/index.html
hierarchicalforecast/src/core.html
hierarchicalforecast/src/evaluation.html
hierarchicalforecast/src/methods.html
hierarchicalforecast/src/probabilistic_methods.html
hierarchicalforecast/src/utils.html
index
mlforecast/auto.html
mlforecast/callbacks.html
mlforecast/compat
mlforecast/core.html
mlforecast/distributed.forecast.html
mlforecast/distributed.models.dask.lgb.html
mlforecast/distributed.models.dask.xgb.html
mlforecast/distributed.models.ray.lgb.html
mlforecast/distributed.models.ray.xgb.html
mlforecast/distributed.models.spark.lgb.html
mlforecast/distributed.models.spark.xgb.html
mlforecast/docs/getting-started/end_to_end_walkthrough.html
mlforecast/docs/getting-started/install.html
mlforecast/docs/getting-started/quick_start_distributed.html
mlforecast/docs/getting-started/quick_start_local.html
mlforecast/docs/how-to-guides/analyzing_models.html
mlforecast/docs/how-to-guides/cross_validation.html
mlforecast/docs/how-to-guides/custom_date_features.html
mlforecast/docs/how-to-guides/custom_training.html
mlforecast/docs/how-to-guides/exogenous_features.html
mlforecast/docs/how-to-guides/hyperparameter_optimization.html
mlforecast/docs/how-to-guides/lag_transforms_guide.html
mlforecast/docs/how-to-guides/mlflow.html
mlforecast/docs/how-to-guides/one_model_per_horizon.html
mlforecast/docs/how-to-guides/predict_callbacks.html
mlforecast/docs/how-to-guides/predict_subset.html
mlforecast/docs/how-to-guides/prediction_intervals.html
mlforecast/docs/how-to-guides/sample_weights.html
mlforecast/docs/how-to-guides/sklearn_pipelines.html
mlforecast/docs/how-to-guides/target_transforms_guide.html
mlforecast/docs/how-to-guides/training_with_numpy.html
mlforecast/docs/how-to-guides/transfer_learning.html
mlforecast/docs/how-to-guides/transforming_exog.html
mlforecast/docs/tutorials/electricity_load_forecasting.html
mlforecast/docs/tutorials/electricity_peak_forecasting.html
mlforecast/docs/tutorials/prediction_intervals_in_forecasting_models.html
mlforecast/feature_engineering.html
mlforecast/forecast.html
mlforecast/grouped_array
mlforecast/index.html
mlforecast/lag_transforms.html
mlforecast/lgb_cv.html
mlforecast/optimization.html
mlforecast/target_transforms.html
mlforecast/utils.html
neuralforecast/common.base_auto.html
neuralforecast/common.base_model
neuralforecast/common.model_checks.html
neuralforecast/common.modules.html
neuralforecast/common.scalers.html
neuralforecast/compat
neuralforecast/core.html
neuralforecast/docs/api-reference/neuralforecast_map.html
neuralforecast/docs/capabilities/cross_validation.html
neuralforecast/docs/capabilities/exogenous_variables.html
neuralforecast/docs/capabilities/hyperparameter_tuning.html
neuralforecast/docs/capabilities/objectives.html
neuralforecast/docs/capabilities/overview.html
neuralforecast/docs/capabilities/predictinsample.html
neuralforecast/docs/capabilities/save_load_models.html
neuralforecast/docs/capabilities/time_series_scaling.html
neuralforecast/docs/getting-started/datarequirements.html
neuralforecast/docs/getting-started/installation.html
neuralforecast/docs/getting-started/introduction.html
neuralforecast/docs/getting-started/quickstart.html
neuralforecast/docs/tutorials/adding_models.html
neuralforecast/docs/tutorials/comparing_methods.html
neuralforecast/docs/tutorials/configure_optimizers.html
neuralforecast/docs/tutorials/conformal_prediction.html
neuralforecast/docs/tutorials/cross_validation.html
neuralforecast/docs/tutorials/distributed_neuralforecast.html
neuralforecast/docs/tutorials/explainability
neuralforecast/docs/tutorials/forecasting_tft.html
neuralforecast/docs/tutorials/getting_started_complete.html
neuralforecast/docs/tutorials/hierarchical_forecasting.html
neuralforecast/docs/tutorials/intermittent_data.html
neuralforecast/docs/tutorials/interpretable_decompositions.html
neuralforecast/docs/tutorials/large_datasets.html
neuralforecast/docs/tutorials/longhorizon_nhits.html
neuralforecast/docs/tutorials/longhorizon_probabilistic.html
neuralforecast/docs/tutorials/longhorizon_transformers.html
neuralforecast/docs/tutorials/multivariate_tsmixer.html
neuralforecast/docs/tutorials/robust_forecasting.html
neuralforecast/docs/tutorials/temporal_classification.html
neuralforecast/docs/tutorials/transfer_learning.html
neuralforecast/docs/tutorials/uncertainty_quantification.html
neuralforecast/docs/tutorials/using_mlflow.html
neuralforecast/docs/use-cases/electricity_peak_forecasting.html
neuralforecast/docs/use-cases/predictive_maintenance.html
neuralforecast/losses.numpy.html
neuralforecast/losses.pytorch.html
neuralforecast/models.autoformer.html
neuralforecast/models.bitcn.html
neuralforecast/models.deepar.html
neuralforecast/models.deepnpts.html
neuralforecast/models.dilated_rnn.html
neuralforecast/models.dlinear.html
neuralforecast/models.fedformer.html
neuralforecast/models.gru.html
neuralforecast/models.hint.html
neuralforecast/models.html
neuralforecast/models.informer.html
neuralforecast/models.itransformer.html
neuralforecast/models.kan.html
neuralforecast/models.lstm.html
neuralforecast/models.mlp.html
neuralforecast/models.mlpmultivariate.html
neuralforecast/models.nbeats.html
neuralforecast/models.nbeatsx.html
neuralforecast/models.nhits.html
neuralforecast/models.nlinear.html
neuralforecast/models.patchtst.html
neuralforecast/models.rmok.html
neuralforecast/models.rnn.html
neuralforecast/models.softs.html
neuralforecast/models.stemgnn.html
neuralforecast/models.tcn.html
neuralforecast/models.tft.html
neuralforecast/models.tide.html
neuralforecast/models.timellm.html
neuralforecast/models.timemixer.html
neuralforecast/models.timesnet.html
neuralforecast/models.timexer.html
neuralforecast/models.tsmixer.html
neuralforecast/models.tsmixerx.html
neuralforecast/models.vanillatransformer.html
neuralforecast/models.xlstm
neuralforecast/tsdataset.html
neuralforecast/utils.html
nixtla/docs/capabilities/capabilities.html
nixtla/docs/capabilities/forecast/categorical_variables.html
nixtla/docs/capabilities/forecast/cross_validation.html
nixtla/docs/capabilities/forecast/custom_loss_function.html
nixtla/docs/capabilities/forecast/exogenous_variables.html
nixtla/docs/capabilities/forecast/finetuning.html
nixtla/docs/capabilities/forecast/forecast.html
nixtla/docs/capabilities/forecast/holidays_special_dates.html
nixtla/docs/capabilities/forecast/irregular_timestamps.html
nixtla/docs/capabilities/forecast/longhorizon.html
nixtla/docs/capabilities/forecast/multiple_series.html
nixtla/docs/capabilities/forecast/prediction_intervals.html
nixtla/docs/capabilities/forecast/quickstart.html
nixtla/docs/capabilities/historical-anomaly-detection/anomaly_detection_date_features.html
nixtla/docs/capabilities/historical-anomaly-detection/anomaly_exogenous.html
nixtla/docs/capabilities/historical-anomaly-detection/confidence_levels.html
nixtla/docs/capabilities/historical-anomaly-detection/historical_anomaly_detection.html
nixtla/docs/capabilities/historical-anomaly-detection/quickstart.html
nixtla/docs/capabilities/online-anomaly-detection/adjusting_detection_process.html
nixtla/docs/capabilities/online-anomaly-detection/online_anomaly_detection.html
nixtla/docs/capabilities/online-anomaly-detection/quickstart.html
nixtla/docs/capabilities/online-anomaly-detection/univariate_vs_multivariate_anomaly_detection.html
nixtla/docs/deployment/azure_ai.html
nixtla/docs/getting-started/azure_quickstart.html
nixtla/docs/getting-started/data_requirements.html
nixtla/docs/getting-started/faq.html
nixtla/docs/getting-started/glossary.html
nixtla/docs/getting-started/introduction.html
nixtla/docs/getting-started/polars_quickstart.html
nixtla/docs/getting-started/pricing.html
nixtla/docs/getting-started/quickstart.html
nixtla/docs/getting-started/setting_up_your_api_key.html
nixtla/docs/getting-started/why_timegpt.html
nixtla/docs/reference/date_features.html
nixtla/docs/reference/excel_addin.html
nixtla/docs/reference/nixtla_client.html
nixtla/docs/reference/nixtlar.html
nixtla/docs/tutorials/anomaly_detection.html
nixtla/docs/tutorials/bounded_forecasts.html
nixtla/docs/tutorials/categorical_variables.html
nixtla/docs/tutorials/computing_at_scale.html
nixtla/docs/tutorials/computing_at_scale_dask_distributed.html
nixtla/docs/tutorials/computing_at_scale_ray_distributed.html
nixtla/docs/tutorials/computing_at_scale_spark_distributed.html
nixtla/docs/tutorials/cross_validation.html
nixtla/docs/tutorials/exogenous_variables.html
nixtla/docs/tutorials/finetune_depth_finetuning.html
nixtla/docs/tutorials/finetuning.html
nixtla/docs/tutorials/hierarchical_forecasting.html
nixtla/docs/tutorials/historical_forecast.html
nixtla/docs/tutorials/holidays.html
nixtla/docs/tutorials/how_to_improve_forecast_accuracy.html
nixtla/docs/tutorials/longhorizon.html
nixtla/docs/tutorials/loss_function_finetuning.html
nixtla/docs/tutorials/missing_values.html
nixtla/docs/tutorials/multiple_series.html
nixtla/docs/tutorials/reusing_finetuned_models.html
nixtla/docs/tutorials/shap_values.html
nixtla/docs/tutorials/special_topics.html
nixtla/docs/tutorials/temporalhierarchical.html
nixtla/docs/tutorials/training.html
nixtla/docs/tutorials/uncertainty_quantification.html
nixtla/docs/tutorials/uncertainty_quantification_with_prediction_intervals.html
nixtla/docs/tutorials/uncertainty_quantification_with_quantile_forecasts.html
nixtla/docs/tutorials/validation.html
nixtla/docs/use-cases/bitcoin_price_prediction.html
nixtla/docs/use-cases/electricity_demand.html
nixtla/docs/use-cases/forecasting_web_traffic.html
nixtla/docs/use-cases/intermittent_demand.html
nixtla/docs/use-cases/what_if_pricing_scenarios_in_retail.html
nixtla/src/date_features.html
nixtla/src/nixtla_client.html
nixtla/src/utils.html
statsforecast/blog/index
statsforecast/blog/posts/2022-10-05-distributed-fugue/index
statsforecast/docs/contribute/contribute
statsforecast/docs/contribute/docs
statsforecast/docs/contribute/issue-labels
statsforecast/docs/contribute/issues
statsforecast/docs/contribute/step-by-step
statsforecast/docs/contribute/techstack
statsforecast/docs/distributed/dask.html
statsforecast/docs/distributed/ray.html
statsforecast/docs/distributed/spark.html
statsforecast/docs/experiments/amazonstatsforecast.html
statsforecast/docs/experiments/autoarima_vs_prophet.html
statsforecast/docs/experiments/ets_ray_m5.html
statsforecast/docs/experiments/prophet_spark_m5.html
statsforecast/docs/getting-started/getting_started_complete.html
statsforecast/docs/getting-started/getting_started_complete_polars.html
statsforecast/docs/getting-started/getting_started_short.html
statsforecast/docs/getting-started/installation.html
statsforecast/docs/how-to-guides/automatic_forecasting.html
statsforecast/docs/how-to-guides/exogenous.html
statsforecast/docs/how-to-guides/generating_features.html
statsforecast/docs/how-to-guides/migrating_R
statsforecast/docs/how-to-guides/numba_cache.html
statsforecast/docs/how-to-guides/sklearn_models.html
statsforecast/docs/models/adida.html
statsforecast/docs/models/arch.html
statsforecast/docs/models/arima.html
statsforecast/docs/models/autoarima.html
statsforecast/docs/models/autoces.html
statsforecast/docs/models/autoets.html
statsforecast/docs/models/autoregressive.html
statsforecast/docs/models/autotheta.html
statsforecast/docs/models/crostonclassic.html
statsforecast/docs/models/crostonoptimized.html
statsforecast/docs/models/crostonsba.html
statsforecast/docs/models/dynamicoptimizedtheta.html
statsforecast/docs/models/dynamicstandardtheta.html
statsforecast/docs/models/garch.html
statsforecast/docs/models/holt.html
statsforecast/docs/models/holtwinters.html
statsforecast/docs/models/imapa.html
statsforecast/docs/models/mfles.html
statsforecast/docs/models/multipleseasonaltrend.html
statsforecast/docs/models/optimizedtheta.html
statsforecast/docs/models/seasonalexponentialsmoothing.html
statsforecast/docs/models/seasonalexponentialsmoothingoptimized.html
statsforecast/docs/models/simpleexponentialoptimized.html
statsforecast/docs/models/simpleexponentialsmoothing.html
statsforecast/docs/models/standardtheta.html
statsforecast/docs/models/tsb.html
statsforecast/docs/tutorials/anomalydetection.html
statsforecast/docs/tutorials/conformalprediction.html
statsforecast/docs/tutorials/crossvalidation.html
statsforecast/docs/tutorials/electricityloadforecasting.html
statsforecast/docs/tutorials/electricitypeakforecasting.html
statsforecast/docs/tutorials/garch_tutorial.html
statsforecast/docs/tutorials/intermittentdata.html
statsforecast/docs/tutorials/mlflow.html
statsforecast/docs/tutorials/multipleseasonalities.html
statsforecast/docs/tutorials/statisticalneuralmethods.html
statsforecast/docs/tutorials/uncertaintyintervals.html
statsforecast/index.html
statsforecast/src/adapters.prophet.html
statsforecast/src/arima.html
statsforecast/src/ces.html
statsforecast/src/core/core.html
statsforecast/src/core/distributed.fugue.html
statsforecast/src/core/models.html
statsforecast/src/core/models_intro
statsforecast/src/distributed.core.html
statsforecast/src/distributed.multiprocess.html
statsforecast/src/ets.html
statsforecast/src/feature_engineering.html
statsforecast/src/garch.html
statsforecast/src/mfles.html
statsforecast/src/mstl.html
statsforecast/src/tbats.html
statsforecast/src/theta.html
statsforecast/src/utils.html
utilsforecast/compat
utilsforecast/data.html
utilsforecast/evaluation.html
utilsforecast/feature_engineering.html
utilsforecast/grouped_array
utilsforecast/index.html
utilsforecast/losses.html
utilsforecast/plotting.html
utilsforecast/preprocessing.html
utilsforecast/processing
utilsforecast/validation.html
/statsforecast/docs/getting-started/0_Installation
/statsforecast/docs/getting-started/1_Getting_Started_short
/statsforecast/docs/getting-started/2_Getting_Started_complete
/statsforecast/docs/tutorials/AnomalyDetection
/statsforecast/docs/tutorials/CrossValidation
/statsforecast/docs/tutorials/MultipleSeasonalities
/statsforecast/docs/tutorials/ElectricityPeakForecasting
/statsforecast/docs/tutorials/IntermittentData
/statsforecast/docs/how-to-guides/Exogenous
coreforecast
hierarchicalforecast/examples
statsforecast/blog
statsforecast/blog/posts/2022-10-05-distributed-fugue
Page revalidation complete
Successfully deleted stale tracked asset(s)
Queued update of llms-full.txt
Skipping Vercel revalidation (subdomain not in revalidation list)
Prewarming paths
Updated Cloudflare deployment cache
Loading