rqr_berg: Randomized quantile residuals in the BerG regression model
In rdmatheus/bergrm: BerG Regression Model for Count Data
Description
Usage
Arguments
Value
Author(s)
References
View source: R/berg_diagnostic.R
Description
Randomized quantile residuals resulting from the fit of
the BerG regression model.
Usage
1
rqr_berg(y, mu, phi)
Arguments
y
vector; observed values of the response variable.
mu
fitted values.
phi
fitted values for dispersion index.
Value
Randomized quantile residuals resulting from the fit of
the BerG regression model.
Author(s)
Rodrigo M. R. Medeiros <rodrigo.matheus@live.com>
References
Bourguignon, M. and Medeiros, R. (2019). A flexibe, simple and useful regression model for fitting count data.
Dunn, P. K., and Smyth, G. K. (1996). Randomized quantile residuals. Journal of Computational and Graphical Statistics, 5, 236-244.
rdmatheus/bergrm documentation built on Oct. 1, 2020, 4:38 a.m.
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Description Usage Arguments Value Author(s) References
View source: R/berg_diagnostic.R
Description
Randomized quantile residuals resulting from the fit of the BerG regression model.
Usage
1 | rqr_berg(y, mu, phi)
|
Arguments
y |
vector; observed values of the response variable. |
mu |
fitted values. |
phi |
fitted values for dispersion index. |
Value
Randomized quantile residuals resulting from the fit of the BerG regression model.
Author(s)
Rodrigo M. R. Medeiros <rodrigo.matheus@live.com>
References
Bourguignon, M. and Medeiros, R. (2019). A flexibe, simple and useful regression model for fitting count data. Dunn, P. K., and Smyth, G. K. (1996). Randomized quantile residuals. Journal of Computational and Graphical Statistics, 5, 236-244.
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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