bayesianRegression: MCMC Samples of Bayesian Linear Regression
In dhelkey/dghrank: Construct Draper-Gittoes-Helkey Institution Rankings
View source: R/bayesianRegression.R
Description
bayesianRegression generates MCMC samples from Bayesian Linear Regression.
Assumes prior mean centered at 0.
Written by Daniel Kirsner
Usage
1
bayesianRegression(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/dghrank documentation built on April 21, 2020, 9:11 a.m.
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View source: R/bayesianRegression.R
Description
bayesianRegression generates MCMC samples from Bayesian Linear Regression.
Assumes prior mean centered at 0.
Written by Daniel Kirsner
Usage
1 | bayesianRegression(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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