• Hailfinder

  • Referenced in 21 articles [sw35867]
  • both experience and physical understanding, to forecast severe weather in Northeastern Colorado. The system ... basis of many past investigations of probabilistic forecasting. The design of Hailfinder provides a variety...
  • ProbForecastGOP

  • Referenced in 11 articles [sw11356]
  • ProbForecastGOP: Probabilistic weather forecast using the GOP method. The ProbForecastGOP package contains a main function ... ProbForecastGOP and other functions, to produce probabilistic weather forecasts of weather fields using the Geostatistical...
  • DeepAR

  • Referenced in 5 articles [sw38790]
  • DeepAR: Probabilistic Forecasting with Autoregressive Recurrent Networks. Probabilistic forecasting, i.e. estimating the probability distribution ... business processes. In retail businesses, for example, forecasting demand is crucial for having the right ... DeepAR, a methodology for producing accurate probabilistic forecasts, based on training an auto regressive recurrent...
  • scoringRules

  • Referenced in 5 articles [sw21375]
  • Evaluating probabilistic forecasts with the R package scoringRules. Probabilistic forecasts in the form of probability ... sources can be used to produce probabilistic forecasts. Hence, evaluating and selecting among competing methods ... provides functionality for comparative evaluation of probabilistic models based on proper scoring rules, covering...
  • ensembleBMA

  • Referenced in 4 articles [sw21377]
  • package ensembleBMA: Probabilistic Forecasting using Ensembles and Bayesian Model Averaging. Bayesian Model Averaging to create ... probabilistic forecasts from ensemble forecasts and weather observations...
  • verification

  • Referenced in 2 articles [sw21378]
  • Utilities for verifying discrete, continuous and probabilistic forecasts, and forecasts expressed as parametric distributions...
  • ensembleMOS

  • Referenced in 2 articles [sw21381]
  • Ensemble Model Output Statistics to create probabilistic forecasts from ensemble forecasts and weather observations...
  • properscoring

  • Referenced in 1 article [sw21380]
  • Python. Proper scoring rules for evaluating probabilistic forecasts in Python. Evaluation methods that are “strictly ... methods for accessing the accuracy of probabilistic forecasts. In particular, these rules are often used...
  • gamFactory

  • Referenced in 1 article [sw41465]
  • household level, which is more challenging than forecasting aggregate demand, due to the lower signal ... propose a new ensemble method for probabilistic forecasting which borrows strength across the households while...
  • PyTorchTS

  • Referenced in 2 articles [sw38190]
  • PyTorchTS is a PyTorch Probabilistic Time Series forecasting framework which provides state...
  • ensAR

  • Referenced in 1 article [sw28376]
  • package ensAR: Probabilistic Temperature Forecasting with a Heteroscedastic Autoregressive Ensemble Postprocessing model. Weather prediction today...
  • Pysteps

  • Referenced in 1 article [sw35887]
  • source and community-driven Python library for probabilistic precipitation nowcasting, i.e. short-term ensemble prediction ... accessible platform for practitioners ranging from weather forecasters to hydrologists. The pysteps library supports standard ... nowcasts and methods for deterministic, probabilistic, and neighbourhood forecast verification...
  • xskillscore

  • Referenced in 1 article [sw37584]
  • xskillscore: Metrics for verifying forecasts. xskillscore is an open source project and Python package that ... verification metrics of deterministic (and probabilistic from properscoring) forecasts with xarray...
  • PyFlux

  • Referenced in 2 articles [sw35431]
  • output for forecasting and retrospection. Users can build a full probabilistic model where the data ... advantage of a probabilistic approach is that it gives a more complete picture of uncertainty ... important for time series tasks such as forecasting. Alternatively, for speed, users can simply...
  • GluonTS

  • Referenced in 2 articles [sw35434]
  • GluonTS: probabilistic and neural time series modeling in Python. We introduce the Gluon Time Series ... series modeling for ubiquitous tasks, such as forecasting and anomaly detection. GluonTS simplifies the time...
  • MET

  • Referenced in 1 article [sw21376]
  • using output from the Weather Research and Forecasting (WRF) modeling system but may be applied ... intensity-scale decomposition approaches; Ensemble and probabilistic verification methods comparing gridded model data to point...
  • ANSYS

  • Referenced in 704 articles [sw00044]
  • ANSYS offers a comprehensive software suite that spans...
  • BARON

  • Referenced in 354 articles [sw00066]
  • BARON is a computational system for solving nonconvex...
  • CGAL

  • Referenced in 394 articles [sw00118]
  • The goal of the CGAL Open Source Project...
  • LSQR

  • Referenced in 394 articles [sw00530]
  • Algorithm 583: LSQR: Sparse Linear Equations and Least...