probitFit: MCMC Samples for Probit Regression
In dhelkey/dgrank: Construct Draper-Gittoes Rankings of Institutions
Description
probitFit generates MCMCM samples of Probit regression, following
the data-augmentation Gibbs sampler of Albert and Chib (1993).
Rquires truncnorm package to sample from truncated normal.
Assumes prior centered at 0, and diagonal prior covariance structure.
Assumes response y is coded as 0-1.
Usage
1
probitFit(y, X, prior_var_vec, iters = 100)
Arguments
y
<nX1> observed data vector
X
<nXp> design matrix (takes objects of class matrix or sparce Matrix)
prior_var_vec
<px1> prior variance vector
iters
Integer; number of desired output iterations
dhelkey/dgrank documentation built on May 12, 2019, 5:24 p.m.
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Description
probitFit generates MCMCM samples of Probit regression, following
the data-augmentation Gibbs sampler of Albert and Chib (1993).
Rquires truncnorm package to sample from truncated normal.
Assumes prior centered at 0, and diagonal prior covariance structure.
Assumes response y is coded as 0-1.
Usage
1 | probitFit(y, X, prior_var_vec, iters = 100)
|
Arguments
y |
<nX1> observed data vector |
X |
<nXp> design matrix (takes objects of class matrix or sparce Matrix) |
prior_var_vec |
<px1> prior variance vector |
iters |
Integer; number of desired output iterations |
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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