Skip to content

fix broken url

c74d1aa
Select commit
Loading
Failed to load commit list.
Draft

Old docs #25

fix broken url
c74d1aa
Select commit
Loading
Failed to load commit list.
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