# NOT RUN {
# Generate 100 observations from a zero-modified normal distribution
# with mean=4, sd=2, and p.zero=0.5, then estimate the parameters and
# the 80th and 90th percentiles.
# (Note: the call to set.seed simply allows you to reproduce this example.)
set.seed(250)
dat <- rzmnorm(100, mean = 4, sd = 2, p.zero = 0.5)
eqzmnorm(dat, p = c(0.8, 0.9))
#Results of Distribution Parameter Estimation
#--------------------------------------------
#
#Assumed Distribution: Zero-Modified Normal
#
#Estimated Parameter(s): mean = 4.037732
# sd = 1.917004
# p.zero = 0.450000
# mean.zmnorm = 2.220753
# sd.zmnorm = 2.465829
#
#Estimation Method: mvue
#
#Estimated Quantile(s): 80'th %ile = 4.706298
# 90'th %ile = 5.779250
#
#Quantile Estimation Method: Quantile(s) Based on
# mvue Estimators
#
#Data: dat
#
#Sample Size: 100
#----------
# Compare the estimated quantiles with the true quantiles
qzmnorm(mean = 4, sd = 2, p.zero = 0.5, p = c(0.8, 0.9))
#[1] 4.506694 5.683242
#----------
# Clean up
rm(dat)
# }
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