logistol.int {tolerance} | R Documentation |
Provides 1-sided tolerance intervals for data distributed according to a logistic or log-logistic distribution.
logistol.int(x, alpha = 0.05, P = 0.99, log.log = FALSE)
x |
A vector of data which is distributed according to a logistic or log-logistic distribution. |
alpha |
The level chosen such that 1-alpha is the confidence level. |
P |
The proportion of the population to be covered by this tolerance interval. |
log.log |
If TRUE , then the data is considered to be from a log-logistic distribution, in which
case the output gives tolerance intervals for the log-logistic distribution. The default is FALSE . |
Recall that if the random variable X is distributed according to a log-logistic distribution, then the random variable Y = ln(X) is distributed according to a logistic distribution.
logistol.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. |
1-sided.upper |
The 1-sided upper tolerance bound. |
Balakrishnan, N. (1992), Handbook of the Logistic Distribution, Marcel Dekker, Inc.
Hall, I. J. (1975), One-Sided Tolerance Limits for a Logistic Distribution Based on Censored Samples, Biometrics, 31, 873–880.
## 90%/95% 1-sided logistic tolerance intervals for a sample ## of size 20. set.seed(100) x <- rlogis(20, 5, 1) out <- logistol.int(x = x, alpha = 0.10, P = 0.95, log.log = FALSE) out plottol(out, x, plot.type = "control", side = "two", x.lab = "Logistic Data")