InfoWorld

An introduction to time series forecasting

Time series forecasts are used to predict a future value or a classification at a particular point in time. Here’s a brief overview of their common uses and how they are developed. Industries from ...
InfoWorld

3 forecasts about time-series forecasting

Pre-trained foundation models are making time-series forecasting more accessible and available, unlocking its benefits for smaller organizations with limited resources. Over the last year, we’ve seen ...
ascopubs.org

Time Series Prediction of Lung Cancer Death Rates on the Basis of SEER Data

This study used SEER data from 1975 to 2018 and included 545,486 patients with lung cancer. The best parameters for ARIMA are ARIMA (p, d, q) = (0, 2, 2). In addition, the best parameter for SES was α ...
San Francisco Fed

The Anatomy of Out-of-Sample Forecasting Accuracy

We introduce the performance-based Shapley value (PBSV) to measure the contributions of individual predictors to the out-of-sample loss for time-series forecasting models. Our new metric allows a ...
VentureBeat

IBM Granite 3.2 uses conditional reasoning, time series forecasting and document vision to tackle challenging enterprise use cases

In the wake of the disruptive debut of DeepSeek-R1, reasoning models have been all the rage so far in 2025. IBM is now joining the party, with the debut today of its Granite 3.2 large language model ...