# NOT RUN {
# Generate 20 observations from a logistic distribution with
# parameters location=0 and scale=1, then estimate the parameters
# and construct a 90% confidence interval for the location parameter.
# (Note: the call to set.seed simply allows you to reproduce this example.)
set.seed(250)
dat <- rlogis(20)
elogis(dat, ci = TRUE, conf.level = 0.9)
#Results of Distribution Parameter Estimation
#--------------------------------------------
#
#Assumed Distribution: Logistic
#
#Estimated Parameter(s): location = -0.2181845
# scale = 0.8152793
#
#Estimation Method: mle
#
#Data: dat
#
#Sample Size: 20
#
#Confidence Interval for: location
#
#Confidence Interval Method: Normal Approximation
# (t Distribution)
#
#Confidence Interval Type: two-sided
#
#Confidence Level: 90%
#
#Confidence Interval: LCL = -0.7899382
# UCL = 0.3535693
#----------
# Clean up
#---------
rm(dat)
# }
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