Vnnman (1995) proposed a superstructure Cp (u, v) of capability indices for processes with normal distributions, which include Cp, Cpk, Cpm, and Cpmk as special cases. Pearn and Chen (1997) considered a generalization of Cp (u, v), called CNp (u, v), to cover processes with non normal distributions. Pearn and Chen (1997) also proposed a sample percentile estimator for the generalization CNp (u, v). In this article, we investigate the performance of the sample percentile estimator. We perform some simulation study, which covers the normal distribution and various non normal distributions including the uniform distribution, chi-square distribution, student's t distributions, F distribution, beta distribution, gamma distribution, Weibull distribution, lognormal distribution, triangular distribution, and Laplace distribution, with selected parameter values. Extensive simulation results, comparisons, and analysis are provided.
|Number of pages||41|
|Journal||Communications in Statistics: Simulation and Computation|
|State||Published - 1 May 2007|
- Flexible capability indices
- Non normal distributions
- Relative bias
- Sample percentile estimator