Qest (version 1.0.1)

summary.Qest: Summarizing Q-estimators

Description

Summary method for class “Qest”.

Usage

# S3 method for Qest
summary(object, covar = FALSE, ...)

Value

The function summary.Qest computes and returns a list of summary statistics of the fitted model given in object, using the "call" and "terms" from its argument, plus

coefficients

a matrix with 4 columns reporting the estimated coefficients, the estimated standard errors, the corresponding z-values (coef/se), and the two-sided p-values.

obj.function

the value of the minimized loss function (see Qest for details).

n

the number of observations.

npar

the number of free parameters.

iter

the number of iterations.

covar

only if covar = TRUE, the estimated covariance matrix.

call

the matched call.

type

a character string defined as follows: "c" for right-censored data; "ct" for left-truncated, right-censored data; and "u" otherwise.

Arguments

object

an object of class “Qest”.

covar

logical; if TRUE, the variance covariance matrix of the estimated parameters is returned.

...

for future methods.

Author

Gianluca Sottile <[e-mail]>

Details

This function returns a summary of the most relevant information on model parameters, standard errors, and convergence status.

References

Sottile G, and Frumento P (2022). Robust estimation and regression with parametric quantile functions. Computational Statistics and Data Analysis. <doi:10.1016/j.csda.2022.107471>

See Also

Qest, for model fitting.

Examples

# Quantile function of an Exponential model
Qexp <- function(theta, tau, data){
  qexp(tau, exp(theta))
}

y <- rexp(100, exp(1))
m1 <- Qest(y ~ 1, Q = Qexp, start = NA)
summary(m1)
summary(m1, covar = TRUE)