Testing the Drift-Diffusion Model

 0 Người đánh giá. Xếp hạng trung bình 0

Tác giả: Drew Fudenberg, Whitney K Newey, Philipp Strack, Tomasz Strzalecki

Ngôn ngữ: eng

Ký hiệu phân loại: 174.28 Experimentation

Thông tin xuất bản: 2019

Mô tả vật lý:

Bộ sưu tập: Metadata

ID: 163229

The drift diffusion model (DDM) is a model of sequential sampling with diffusion (Brownian) signals, where the decision maker accumulates evidence until the process hits a stopping boundary, and then stops and chooses the alternative that corresponds to that boundary. This model has been widely used in psychology, neuroeconomics, and neuroscience to explain the observed patterns of choice and response times in a range of binary choice decision problems. This paper provides a statistical test for DDM's with general boundaries. We first prove a characterization theorem: we find a condition on choice probabilities that is satisfied if and only if the choice probabilities are generated by some DDM. Moreover, we show that the drift and the boundary are uniquely identified. We then use our condition to nonparametrically estimate the drift and the boundary and construct a test statistic.
Tạo bộ sưu tập với mã QR

THƯ VIỆN - TRƯỜNG ĐẠI HỌC CÔNG NGHỆ TP.HCM

ĐT: (028) 36225755 | Email: tt.thuvien@hutech.edu.vn

Copyright @2024 THƯ VIỆN HUTECH