tidy_local_influence: Tidy Functions for Local Influence Diagnostics

In mixpoissonreg: Mixed Poisson Regression for Overdispersed Count Data

Description

Functions to provide tidy outputs or ggplot2-based plots of local influence diagnostics.

Usage

local_influence_autoplot(model, ...)

tidy_local_influence(model, ...)

local_influence_benchmarks(model, ...)

Arguments

model	A model object for which local influence diagnostics are desired.
...	additional arguments to be passed.

Details

Local influence diagnostics were first introduced by Cook (1986), where several perturbation schemes were introduced and normal curvatures were obtained. Poon and Poon (1999) introduced the conformal normal curvature, which has nice properties and takes values on the unit interval [0,1]. Zhu and Lee (2001) following Cook (1986) and Poon and Poon (1999) introduced normal and conformal normal curvatures for EM-based models.

Value

The tidy_local_influence method returns a tibble containing the resulting perturbation schemes as columns. The local_influence_benchmarks method returns a tibble with the benchmarks as columns. The local_influence_autoplot method is called for its side effects.

References

Cook, R. D. (1986) Assessment of Local Influence. Journal of the Royal Statistical Society. Series B (Methodological), Vol. 48, pp.133-169. https://rss.onlinelibrary.wiley.com/doi/10.1111/j.2517-6161.1986.tb01398.x

Poon, W.-Y. and Poon, Y.S. (1999) Conformal normal curvature and assessment of local influence. Journal of the Royal Statistical Society. Series B (Methodological), Vol. 61, pp.51-61. https://rss.onlinelibrary.wiley.com/doi/abs/10.1111/1467-9868.00162

Zhu, H.-T. and Lee, S.-Y. (2001) Local influence for incomplete data models. Journal of the Royal Statistical Society. Series B (Methodological), Vol. 63, pp.111-126. https://rss.onlinelibrary.wiley.com/doi/abs/10.1111/1467-9868.00279

mixpoissonreg documentation built on March 11, 2021, 1:07 a.m.