InfoWorld

Time series forecasting with ARMA and InfluxDB

Autoregressive moving average models have a number of advantages including simplicity. Here’s how to use an ARMA model with InfluxDB. An ARMA or autoregressive moving average model is a forecasting ...
Nature

A comparative evaluation of time-series models for forecasting inpatient deaths and discharges against medical advice

Forecasting inpatient mortality (IM) and discharges against medical advice (DAMA) provides essential insights for healthcare quality monitoring and hospital management. This study compared six ...
Nature

Two forecasting model selection methods based on time series image feature augmentation

Accurate forecasting of food commodity prices is one of the most challenging yet crucial tasks for agricultural economists. Timely and reliable price predictions not only support market participants ...
Investopedia

Understanding Time Series: Analyzing Data Trends Over Time

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...
InfoWorld

Time series forecasting with XGBoost and InfluxDB

XGBoost is a popular open source machine learning library that can be used to solve all kinds of prediction problems. Here’s how to use XGBoost with InfluxDB. XGBoost is an open source machine ...