poistol.int | R Documentation |
Provides 1-sided or 2-sided tolerance intervals for Poisson random variables. From a statistical quality control perspective, these limits bound the number of occurrences (which follow a Poisson distribution) in a specified future time period.
poistol.int(x, n, m = NULL, alpha = 0.05, P = 0.99, side = 1,
method = c("TAB", "LS", "SC", "CC", "VS", "RVS",
"FT", "CSC"))
x |
The number of occurrences of the event in time period |
n |
The time period of the original measurements. |
m |
The specified future length of time. If |
alpha |
The level chosen such that |
P |
The proportion of occurrences in future time lengths of size |
side |
Whether a 1-sided or 2-sided tolerance interval is required (determined by |
method |
The method for calculating the lower and upper confidence bounds, which are used in the calculation
of the tolerance bounds. The default method is |
poistol.int
returns a data frame with items:
alpha |
The specified significance level. |
P |
The proportion of occurrences in future time periods of length |
lambda.hat |
The mean occurrence rate per unit time, calculated by |
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 |
Barker, L. (2002), A Comparison of Nine Confidence Intervals for a Poisson Parameter When the Expected Number of Events Is \le 5
, The American Statistician, 56, 85–89.
Freeman, M. F. and Tukey, J. W. (1950), Transformations Related to the Angular and the Square Root, Annals of Mathematical Statistics, 21, 607–611.
Hahn, G. J. and Chandra, R. (1981), Tolerance Intervals for Poisson and Binomial Variables, Journal of Quality Technology, 13, 100–110.
Poisson
, umatol.int
## 95%/90% 1-sided Poisson tolerance limits for future
## occurrences in a period of length 3. All seven methods
## are presented for comparison.
poistol.int(x = 45, n = 9, m = 3, alpha = 0.05, P = 0.90,
side = 1, method = "TAB")
poistol.int(x = 45, n = 9, m = 3, alpha = 0.05, P = 0.90,
side = 1, method = "LS")
poistol.int(x = 45, n = 9, m = 3, alpha = 0.05, P = 0.90,
side = 1, method = "SC")
poistol.int(x = 45, n = 9, m = 3, alpha = 0.05, P = 0.90,
side = 1, method = "CC")
poistol.int(x = 45, n = 9, m = 3, alpha = 0.05, P = 0.90,
side = 1, method = "VS")
poistol.int(x = 45, n = 9, m = 3, alpha = 0.05, P = 0.90,
side = 1, method = "RVS")
poistol.int(x = 45, n = 9, m = 3, alpha = 0.05, P = 0.90,
side = 1, method = "FT")
poistol.int(x = 45, n = 9, m = 3, alpha = 0.05, P = 0.90,
side = 1, method = "CSC")
## 95%/90% 2-sided Poisson tolerance intervals for future
## occurrences in a period of length 15. All seven methods
## are presented for comparison.
poistol.int(x = 45, n = 9, m = 15, alpha = 0.05, P = 0.90,
side = 2, method = "TAB")
poistol.int(x = 45, n = 9, m = 15, alpha = 0.05, P = 0.90,
side = 2, method = "LS")
poistol.int(x = 45, n = 9, m = 15, alpha = 0.05, P = 0.90,
side = 2, method = "SC")
poistol.int(x = 45, n = 9, m = 15, alpha = 0.05, P = 0.90,
side = 2, method = "CC")
poistol.int(x = 45, n = 9, m = 15, alpha = 0.05, P = 0.90,
side = 2, method = "VS")
poistol.int(x = 45, n = 9, m = 15, alpha = 0.05, P = 0.90,
side = 2, method = "RVS")
poistol.int(x = 45, n = 9, m = 15, alpha = 0.05, P = 0.90,
side = 2, method = "FT")
poistol.int(x = 45, n = 9, m = 15, alpha = 0.05, P = 0.90,
side = 2, method = "CSC")
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