influence {PLreg} | R Documentation |
The influence
function provides two influence measures and the generalized
leverage for power logit regression models.
influence(model, graph = TRUE, ...)
model |
fitted model object of class " |
graph |
logical. If |
... |
currently not used. |
influence
returns a list with three objects:
case.weights |
The values of |
totalLI |
The total local influence (see Lesaffre and Verbeke (1998)) |
GL |
The diagonal elements of the generalized leverage matrix. |
Queiroz, F. F. and Ferrari, S. L. P. (2022). Power logit regression for modeling bounded data. arXiv:2202.01697.
PLreg
, residuals.PLreg
, envelope
,
plot.PLreg
data("Firm")
fitPL <- PLreg(firmcost ~ sizelog + indcost | sizelog + indcost,
data = Firm, family = "SLASH", zeta = 2.13)
influence_measures = influence(fitPL, graph = FALSE)
plot(influence_measures$case.weights, type = "h", ylim = c(0,1))
plot(influence_measures$totalLI, type = "h", ylim = c(0,6))
plot(Firm$sizelog, influence_measures$GL, pch = "+")