nptol.int | R Documentation |
Provides 1-sided or 2-sided nonparametric (i.e., distribution-free) tolerance intervals for any continuous data set.
nptol.int(x, alpha = 0.05, P = 0.99, side = 1,
method = c("WILKS", "WALD", "HM", "YM"),
upper = NULL, lower = NULL)
x |
A vector of data which no distributional assumptions are made. The data is only assumed to come from a continuous 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 determining which indices of the ordered observations will be used for the tolerance intervals.
|
upper |
The upper bound of the data. When |
lower |
The lower bound of the data. When |
For the Young-Mathew method, interpolation or extrapolation is performed. When side = 1
, two intervals are given: one based on linear interpolation/extrapolation of order statistics (OS-Based
) and one based on fractional order statistics (FOS-Based
). When side = 2
, only an interval based on linear interpolation/extrapolation of order statistics is given.
nptol.int
returns a data frame with items:
alpha |
The specified significance level. |
P |
The proportion of the population covered by this tolerance interval. |
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 |
Bury, K. (1999), Statistical Distributions in Engineering, Cambridge University Press.
Hahn, G. J. and Meeker, W. Q. (1991), Statistical Intervals: A Guide for Practitioners, Wiley-Interscience.
Wald, A. (1943), An Extension of Wilks' Method for Setting Tolerance Limits, The Annals of Mathematical Statistics, 14, 45–55.
Wilks, S. S. (1941), Determination of Sample Sizes for Setting Tolerance Limits, The Annals of Mathematical Statistics, 12, 91–96.
Young, D. S. and Mathew, T. (2014), Improved Nonparametric Tolerance Intervals Based on Interpolated and Extrapolated Order Statistics, Journal of Nonparametric Statistics, 26, 415–432.
distfree.est
, npregtol.int
## 90%/95% 2-sided nonparametric tolerance intervals for a
## sample of size 200.
set.seed(100)
x <- rlogis(200, 5, 1)
out <- nptol.int(x = x, alpha = 0.10, P = 0.95, side = 1,
method = "WILKS", upper = NULL, lower = NULL)
out
plottol(out, x, plot.type = "both", side = "two", x.lab = "X")
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