Description Usage Arguments Details Value
Caluclate the proposal dens on the log scale Computes proposal density by computing the necessary Jacobian of the transformation from y* to y**
1 2 3 4 5 |
y.prop |
proposed data vector satisfying T(y.prop)=T(y_obs) |
X |
design matrix |
proj |
the projection matrix onto the deviation space (aka the least squares residual space) |
l1obs, |
s1obs observed statsitics |
fn.psi |
custom psi function returning psi(x) or psi'(x) defining M-estimator for location ; default is fn.psi.huber |
fn.chi |
custom chi function returning chi(x) or chi'(x) defining M-estimator for scale; default is fn.chi.prop2 |
n |
|
p |
number of regression coefficients |
Qt |
Q transpose where Q is the orthonormalized X |
Designed for use within fn.one.rep.y
. Two equivalent versions, the second uses fn.attenuation2
and is faster.
The proposal density for y.prop on the log scale (assuming original vector sampled uniformly on unit sphere)
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