This paper provides a non-systematic review of the progress of forecasting in social settings.
It is aimed at someone outside the field of forecasting who wants to understand and …

What will be the global impact of the novel coronavirus (COVID-19)? Answering this
question requires accurate forecasting the spread of confirmed cases as well as analysis of …

The M4 Competition follows on from the three previous M competitions, the purpose of which
was to learn from empirical evidence both how to improve the forecasting accuracy and how …

Anomaly detection for time-series data has been an important research field for a long time.
Seminal work on anomaly detection methods has been focussing on statistical approaches …

This is the first paper in a series of two that synthesizes, compares, and extends methods for
causal inference with longitudinal panel data in a structural equation modeling (SEM) …

With the advent of Big Data, nowadays in many applications databases containing large
quantities of similar time series are available. Forecasting time series in these domains with …

Classifying forecasting methods as being either of a “machine learning” or “statistical” nature
has become commonplace in parts of the forecasting literature and community, as …

Od Yogiego Berry do Henriego Poincarégo Rozdział 10: SKANDAL PROGNOZOWANIA O
niesprecyzowanej liczbie kochanków carycy Katarzyny Powrót ślepoty na Czarne Łabędzie …

The demand for a particular product or service is typically associated with different
uncertainties that can make them volatile and challenging to predict. Demand …

Forecasting competitions are now so widespread that it is often forgotten how controversial
they were when first held, and how influential they have been over the years. I briefly review …