gleverage: Generalized Leverage Values

In betareg: Beta Regression

Description

Compute the generalized leverages values for fitted models.

Usage

gleverage(model, ...)

Arguments

model	a model object.
...	further arguments passed to methods.

Value

gleverage is a new generic for computing generalized leverage values as suggested by Wei, Hu, and Fung (1998). Currently, there is only a method for betareg models, implementing the formulas from Rocha and Simas (2011) which are consistent with the formulas from Ferrari and Cribari-Neto (2004) for the fixed dispersion case.

Currently, the vector of generalized leverages requires computations and storage of order n x n.

References

Ferrari, S.L.P., and Cribari-Neto, F. (2004). Beta Regression for Modeling Rates and Proportions. Journal of Applied Statistics, 31(7), 799–815.

Rocha, A.V., and Simas, A.B. (2011). Influence Diagnostics in a General Class of Beta Regression Models. Test, 20(1), 95–119. doi: 10.1007/s11749-010-0189-z

Wei, B.-C., and Hu, Y.-Q., and Fung, W.-K. (1998). Generalized Leverage and Its Applications. Scandinavian Journal of Statistics, 25, 25–37.

See Also

betareg

Examples

options(digits = 4)
data("GasolineYield", package = "betareg")
gy <- betareg(yield ~ batch + temp, data = GasolineYield)
gleverage(gy)

Example output

     1      2      3      4      5      6      7      8      9     10     11 
0.2167 0.2517 0.3254 0.4542 0.2239 0.3201 0.5271 0.2819 0.3011 0.5066 0.1970 
    12     13     14     15     16     17     18     19     20     21     22 
0.2146 0.3054 0.4397 0.2909 0.3514 0.4049 0.2448 0.3570 0.4840 0.2154 0.1835 
    23     24     25     26     27     28     29     30     31     32 
0.2899 0.4701 0.2910 0.2982 0.5449 0.3677 0.6603 0.3181 0.2557 0.4569 

betareg documentation built on Feb. 10, 2021, 1:07 a.m.