normtol.int | R Documentation |
Provides 1-sided or 2-sided tolerance intervals for data distributed according to either a normal distribution or log-normal distribution.
normtol.int(x, alpha = 0.05, P = 0.99, side = 1,
method = c("HE", "HE2", "WBE", "ELL", "KM",
"EXACT", "OCT"), m = 50, log.norm = FALSE)
x |
A vector of data which is distributed according to either a normal distribution or a log-normal distribution. |
alpha |
The level chosen such that |
P |
The proportion of the population to be covered by this tolerance interval. |
side |
Whether a 1-sided or 2-sided tolerance interval is required (determined by |
method |
The method for calculating the k-factors. The k-factor for the 1-sided tolerance intervals
is performed exactly and thus is the same for the chosen method. |
m |
The maximum number of subintervals to be used in the |
log.norm |
If |
Recall that if the random variable X
is distributed according to a log-normal distribution, then the random variable Y = ln(X)
is
distributed according to a normal distribution.
normtol.int
returns a data frame with items:
alpha |
The specified significance level. |
P |
The proportion of the population covered by this tolerance interval. |
x.bar |
The sample mean. |
1-sided.lower |
The 1-sided lower tolerance bound. This is given only if |
1-sided.upper |
The 1-sided upper tolerance bound. This is given only if |
2-sided.lower |
The 2-sided lower tolerance bound. This is given only if |
2-sided.upper |
The 2-sided upper tolerance bound. This is given only if |
Howe, W. G. (1969), Two-Sided Tolerance Limits for Normal Populations - Some Improvements, Journal of the American Statistical Association, 64, 610–620.
Wald, A. and Wolfowitz, J. (1946), Tolerance Limits for a Normal Distribution, Annals of Mathematical Statistics, 17, 208–215.
Weissberg, A. and Beatty, G. (1969), Tables of Tolerance Limit Factors for Normal Distributions, Technometrics, 2, 483–500.
Normal
, K.factor
## 95%/95% 2-sided normal tolerance intervals for a sample
## of size 100.
set.seed(100)
x <- rnorm(100, 0, 0.2)
out <- normtol.int(x = x, alpha = 0.05, P = 0.95, side = 2,
method = "HE", log.norm = FALSE)
out
plottol(out, x, plot.type = "both", side = "two",
x.lab = "Normal Data")
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