The funding backs continued innovation in production-grade forecasting, anomaly detection, and artificial intelligence.

A simple one-period-ahead and multiperiod-ahead prediction procedure for multivariate time series is suggested, based on the canonical correlation technique. The prediction procedure is direct in the ...

Linear multiregression dynamic models, which combine a graphical representation of a multivariate time series with a state space model, have been shown to be a promising class of models for ...

Dubai, UAE -Qlik®, a global leader in data integration, data quality, analytics, and artificial intelligence (AI), today announced general availability of Multivariate Time Series (MVTS) in Qlik ...

Explainable predictive AI in Qlik Cloud lets teams model real-world drivers and update plans in-app with WriteTable for faster outcomes Planning teams juggle multiple variables that move together, not ...

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 ...

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 ...

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 ...