Projections of COVID-19, in standardized format
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Updated
Jun 7, 2024 - Jupyter Notebook
Projections of COVID-19, in standardized format
Time series analysis in Java
Fetch forecasts from prediction markets/forecasting platforms to make them searchable. Integrate these forecasts into other services.
Golang GRIB2 parser
Toolkit for the estimation of hierarchical Bayesian vector autoregressions. Implements hierarchical prior selection for conjugate priors in the fashion of Giannone, Lenza & Primiceri (2015). Allows for the computation of impulse responses and forecasts and provides functionality for assessing results.
getgfs extracts weather forecast variables from the NOAA GFS forecast with no obscure, platform specific, dependencies
A two-stage predictive machine learning engine that forecasts the on-time performance of flights for 15 different airports in the USA based on data collected in 2016 and 2017.
This is the data scraping & modeling code used for models shown in https://econforecasting.com.
Dynamic Grid Prices for Ecopower
Forecasting the effective reproduction number over short timescales
SARS-CoV-2 variant growth rates and frequency forecasts
This is a web display that shows current weather, weather forecast, Google Calendar Events, Crypto Prices and random quotes. It is built on MiddleManApp, jQuery, SCSS, JavaScript, and basic HTML.
Fisher Matrix codes for IM and cross-correlations
The purpose of this report is to identify the most appropriate model to forecast future unemployment rate in the US using the historical data. We present an in-depth study of the forecasts for the monthly U.S. unemployment rate using various time series models and comparing them to further our understanding of the strengths and deficiencies of t…
This project is to measure the popularity of each league using the search data collected from Google Trends, which give real-time historical data on search words. With this project, it is also possible to compare and forecast how the sports league are trending with respect to each other using three models — trend plus seasonality regression, Hol…
Comparison of Model Output Statistics and Adaptive Regression based on Kalman Filters for the Lorenz-96 Model.
This is an attempt to produce load forecast for an electric grid using historic load and weather data
Generates a daily, city specific forecast for the duration of a user created road trip itinerary.
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