Description Usage Arguments Details Value References See Also Examples
Provides 1-sided or 2-sided tolerance intervals for data distributed according to the Poisson-Lindley distribution.
1 2 | poislindtol.int(x, m = NULL, alpha = 0.05, P = 0.99, side = 1,
...)
|
x |
A vector of raw data which is distributed according to a Poisson-Lindley distribution. |
m |
The number of observations in a future sample for which the tolerance limits will be calculated. By default, |
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. |
side |
Whether a 1-sided or 2-sided tolerance interval is required (determined by |
... |
Additional arguments passed to the |
The discrete Poisson-Lindley distribution is a compound distribution that, potentially, provides a better fit for count data relative to the traditional Poisson and negative binomial distributions. Poisson-Lindley distributions are heavily right-skewed distributions. For most practical applications, one will typically be interested in 1-sided upper bounds.
poislindtol.int
returns a data frame with the following items:
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The specified significance level. |
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The proportion of the population covered by this tolerance interval. |
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MLE for the shape parameter |
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The 1-sided lower tolerance bound. This is given only if |
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The 1-sided upper tolerance bound. This is given only if |
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The 2-sided lower tolerance bound. This is given only if |
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The 2-sided upper tolerance bound. This is given only if |
Naghizadeh Qomi, M., Kiapour, A., and Young, D. S. (2015), Approximate Tolerance Intervals for the Discrete Poisson-Lindley Distribution, Journal of Statistical Computation and Simulation, 86, 841–854.
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