evaluate_ppd: Evaluate the posterior predictive distributions for each...
In JasperHG90/blm: Bayesian linear model
Description
Usage
Arguments
Details
Value
See Also
Description
This function simulates outcome variables for each of the posterior parameters. It then returns the proportion where:
Usage
1
evaluate_ppd(x)
Arguments
x
a blm object
Details
p = y_{\text{simulated}} > y_{\text{observed}}
This allows the user to look for patterns against e.g. the predictors or the outcome. See examples and the reference to Lynch below.
Value
object of class "outliers" is added to the blm object
See Also
Lynch, S. M. (2007). Introduction to applied Bayesian statistics and estimation for social scientists. Springer Science & Business Media. pp.178-182
JasperHG90/blm documentation built on Sept. 4, 2019, 11:16 a.m.
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Description Usage Arguments Details Value See Also
Description
This function simulates outcome variables for each of the posterior parameters. It then returns the proportion where:
Usage
1 | evaluate_ppd(x)
|
Arguments
x |
a blm object |
Details
p = y_{\text{simulated}} > y_{\text{observed}}
This allows the user to look for patterns against e.g. the predictors or the outcome. See examples and the reference to Lynch below.
Value
object of class "outliers" is added to the blm object
See Also
Lynch, S. M. (2007). Introduction to applied Bayesian statistics and estimation for social scientists. Springer Science & Business Media. pp.178-182
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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