Learn R Programming

ssym (version 1.5.1)

extra.parameter: Tool that supports the estimation of the extra parameter.

Description

extra.parameter is used to plot a graph of the behaviour of the overall goodness-of-fit statistic and $-2\textsf{L}(\hat{\theta})$ versus the extra parameter $\zeta$ in the interval/region defined by the arguments lower and upper. These graphs may be used to choosing the extra parameter value.

Usage

extra.parameter(object, lower, upper)

Arguments

object
an object of the class ssym. This object is obtained from the application of ssym.l(), ssym.nl() or ssym.l2()
lower
lower limit(s) of the interest interval/region for the extra parameter.
upper
upper limit(s) of the interest interval/region for the extra parameter.

References

Vanegas, L.H. and Paula, G.A. (2015b) Log-symmetric distributions: statistical properties and parameter estimation. Brazilian Journal of Probability and Statistics (to appear)

Examples

Run this code
###################################################################################
############### Textures of snacks Data - a log-Student-t model  #################
###################################################################################
#data("Snacks", package="ssym")
#fit <- extra.parameter(log(texture) ~ type + ncs(week) | type, data=Snacks,
#        family='Student', xi=10)
#summary(fit)
#
############################ Extra parameter ###########################
#extra.parameter(fit,5,50)

###################################################################################
################## Biaxial Fatigue Data - a Birnbaum-Saunders model   #############
###################################################################################
#data("Biaxial", package="ssym")
#fit <- ssym.nl(log(Life) ~ b1*Work^b2, start=c(b1=16, b2=-0.25),
#                data=Biaxial, family='Sinh-normal', xi=1.54)
#summary(fit)
#
########################### Extra parameter ###########################
#extra.parameter(fit,1.3,1.8)

Run the code above in your browser using DataLab