Latent and observable variables
In statistics, latent variables (from Latin: present participle of lateo 'lie hidden') are variables that can only be inferred indirectly through a mathematical model from other observable variables that can be directly observed or measured. Such latent variable models are used in many disciplines, including engineering, medicine, ecology, physics, machine learning/artificial intelligence, natural language processing, bioinformatics, chemometrics, demography, economics, management, political science, psychology and the social sciences.
Latent and observable variables - Wikipedia Jump to content From Wikipedia, the free encyclopedia Concept in statistics For similar uses, see Hidden variable . In statistics , latent variables (from Latin : present participle of lateo ' lie hidden ' [ citation needed ] ) are variables that can only be inferred indirectly through a mathematical model from other observable variables that can be directly observed or measured . [ 1 ] Such latent variable models are used in many disciplines, including engineering , medicine , ecology , physics , machine learning / artificial intelligence , natural
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