response_scheme: response scheme

In sglg: Fitting Semi-Parametric Generalized log-Gamma Regression Models

response scheme

Description

response_scheme.sglg extracts from a object of class sglg the local influence measures and displays their graphs versus the index of the observations.

Usage

response_scheme(model, ...)

Arguments

model	an object of the class sglg. This object is returned from the call to glg(), sglg(), survglg() or ssurvglg().
...	other arguments.

Author(s)

Carlos Alberto Cardozo Delgado <[e-mail]>

References

Carlos Alberto Cardozo Delgado, Semi-parametric generalized log-gamma regression models. Ph. D. thesis. Sao Paulo University.

Cardozo C.A., Paula G., and Vanegas L. (2022). Generalized log-gamma additive partial linear models with P-spline smoothing. Statistical Papers.

Examples

rows <- 100
columns <- 2
t_beta  <- c(0.5, 2)
t_sigma <- 1
t_lambda <- 1
set.seed(8142031)
x1 <- rbinom(rows, 1, 0.5)
x2 <- runif(columns, 0, 1)
X <- cbind(x1,x2)
error <- rglg(rows, 0, 1, t_lambda)
y1 <- X %*%t_beta + t_sigma * error
data.example <- data.frame(y1,X)
fit1 <- glg(y1 ~ x1 + x2 - 1,data=data.example)
response_scheme(fit1)

sglg documentation built on Nov. 28, 2025, 1:06 a.m.