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“Sequential sampling models” books focus on theories and methods where data or evidence is accumulated over time and a decision is made when a stopping threshold is reached. The category spans statistical sequential analysis (such as sequential probability ratio tests and optimal stopping) and cognitive evidence-accumulation models of choice and response time (including drift-diffusion, race, LBA, and LCA models). Titles typically cover mathematical foundations, parameter estimation and model comparison, experimental and adaptive design, and practical algorithms for fitting and applying these models. Applications include perceptual and value-based decision-making in psychology and neuroscience, clinical trials and A/B testing, industrial quality control, economics, and aspects of machine learning. Overall, it is a home for rigorous and applied works on making fast, reliable decisions under uncertainty via principled sequential evidence gathering.

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