robustloggamma (version 1.0-2.1)

loggammarob.test: Robust inference for the generalized loggamma model.

Description

Robust Tests and confidence intervals for the parameters of the generalized loggamma model.

Usage

loggammarob.test(x, mu = NULL, sigma = NULL, lambda = NULL,
eta = NULL, type = "Wald", conf.level = 0.95, prob = 0.00001)

Arguments

x

list. An object of class 'loggammarob'

mu

numeric. Null value for the location parameter

sigma

numeric. Null value for the scale parameter

lambda

numeric. Null value for the shape parameter

eta

numeric. Null value for E(exp(X)) parameter

type

character. Type of inference, for now only Wald test is performed

conf.level

numeric. Level of the confidence interval.

prob

quantile order of the loggamma to be used in the numerical calculation of the expected Fisher Information.

Value

An object of class 'htest' containing the following components:

statistic:

the value of the t-statistic.

parameter:

the degrees of freedom for the statistic.

p.value:

the p-value for the test.

conf.int:

a confidence interval for the parameter appropriate to the specified alternative hypothesis.

estimate:

the estimate of the parameter(s).

null.value:

the specified hypothesized value of the parameter.

alternative:

a character string describing the alternative hypothesis.

method:

a character string indicating what type of test was performed.

data.name:

a character string giving the name(s) of the data.

Details

If no null values are provided, the function report the test for mu=0, sigma=1 and lambda=0.

References

C. Agostinelli, A. Marazzi and V.J. Yohai (2015) Robust estimates of the generalized loggamma distribution, Technometrics, Volume 56, Issue 1, 2014. DOI: 10.1080/00401706.2013.818578

Agostinelli C., Marazzi A., Yohai V.J., Randriamiharisoa A. (2016). Robust Estimation of the Generalized Loggamma Model: The R Package robustloggamma. Journal of Statistical Software, 70(7), 1-21. doi:10.18637/jss.v070.i07

See Also

loggammarob

Examples

# NOT RUN {
  set.seed(1234)
  x <- sort(rloggamma(n=80, lambda=1))
  res <- loggammarob(x, control=loggammarob.control(lower=0, upper=2, n=30))
  loggammarob.test(res, mu=0) #only location
  loggammarob.test(res, mu=0, sigma=1) #location and scale
  loggammarob.test(res, eta=1) #E(exp(X))
# }