todo: describe the model

`mu`

For the probit toxicity model,

`mu`

contains the prior mean vector`Sigma`

For the probit toxicity model, contains the prior covariance matrix

`sigma2betaW`

For the biomarker model, contains the prior variance factor of the random walk prior. If it is not a single number, it can also contain a vector with elements

`a`

and b for the inverse-gamma prior on`sigma2betaW`

.`sigma2W`

Either a fixed value for the biomarker variance, or a vector with elements

`a`

and`b`

for the inverse-gamma prior parameters.`rho`

Either a fixed value for the correlation (between -1 and 1), or a vector with elements

`a`

and`b`

for the Beta prior on the transformation kappa = (rho + 1) / 2, which is in (0, 1). For example,`a=1,b=1`

leads to a uniform prior on rho.`useRW1`

for specifying the random walk prior on the biomarker level: if

`TRUE`

, RW1 is used, otherwise RW2.`useFixed`

a list with logical value for each of the three parameters

`sigma2betaW`

,`sigma2W`

and`rho`

indicating whether a fixed value is used or not.

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