probitFitk: 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).
Written by Daniel Kirsner
Requires 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
probitFitk(y, X, prior_var_vec, iters = 100, sigmasq = 1)
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
sigmasq
TODO
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).
Written by Daniel Kirsner
Requires 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 | probitFitk(y, X, prior_var_vec, iters = 100, sigmasq = 1)
|
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 |
sigmasq |
TODO |
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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