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Prior Probability

Takeshi Akuhara edited this page Jan 7, 2020 · 16 revisions

Prior Probability

We set the prior probability of each model parameter as follows.

Model parameter Distribution type Tuning parameter
# of layer interfaces Truncated uniform K_MIN, K_MAX
Interface depth Truncated uniform Z_MIN, Z_MAX
S wave velocity perturbation (PRIOR_MODE=1) Laplacian DEV_DVS_PRIOR
P wave velocity perturbation (PRIOR_MODE=1) Laplacian DEV_DVP_PRIOR
S wave velocity perturbation (PRIOR_MODE=2) Gaussian DEV_DVS_PRIOR
P wave velocity perturbation (PRIOR_MODE=2) Gaussian DEV_DVP_PRIOR
Data noise standard deviation Truncated Uniform SIG_MIN, SIG_MAX

Note

There are two choices for velocity perturbation: (1) Laplacian and (2) Gaussian. The former prior tries to produce zero amount perturbation for as many layers as possible, analogous to L1 norm regularization.

Related parameters

For the following notations, please refer to Input files.

  • K_MIN, K_MAX
  • Z_MIN, Z_MAX
  • PRIOR_MODE
  • DEV_DVS_PRIOR
  • DEV_DVP_PRIOR
  • SIG_MIN, SIG_MAX

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