In
statistics,
latent variables (from
Latin:
present participle of
lateo (“lie hidden”), as opposed to
observable variables), are
variables that are not directly observed but are rather inferred (through a
mathematical model) from other variables that are observed (directly measured). Mathematical models that aim to explain observed variables in terms of latent variables are called
latent variable models. Latent variable models are used in many disciplines, including
psychology,
economics,
medicine,
physics,
machine learning/
artificial intelligence,
bioinformatics,
natural language processing,
econometrics,
management and the
social sciences.