Open AccessBayesian Attenuation Regressions: an Application to Mexico City
Author(s) -
Ordaz M.,
Singh S. K.,
Arciniega A.
Publication year - 1994
Publication title -
geophysical journal international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.302
H-Index - 168
eISSN - 1365-246X
pISSN - 0956-540X
DOI - 10.1111/j.1365-246x.1994.tb03936.x
Subject(s) - attenuation , bayesian probability , terminology , acceleration , regression , computer science , bayesian linear regression , linear regression , econometrics , mathematics , bayesian inference , algorithm , statistics , artificial intelligence , machine learning , physics , optics , linguistics , philosophy , classical mechanics
SUMMARY We describe the application of a bayesian linear regression technique to the problem of deriving strong‐motion attenuation relations. This approach provides a conceptual framework for the formal incorporation of knowledge about the involved phenomena that comes from sources other than the observed data ( prior information , according to the bayesian terminology). the procedure produces numerical solutions that are more stable and rational than those obtained from conventional regression schemes. We illustrate the use of the proposed technique with the derivation of attenuation laws for the Fourier acceleration spectrum, as a function of magnitude and distance, at a hill‐zone station in Mexico City.