The likelihood function of ARMA processes with some fixed parameters is considered. An expression for it and a sufficient statistic are obtained. It is shown how the proposed approach can be used to obtain closed form expressions for the likelihood functions of some ARMA models. Applications to parameter estimation, hypothesis testing, speech processing and related problems are discussed
Let F be a life distribution with survival function = 1 - F and finite mean The scaled total time on test transform was introduced by Barlow and Campo (1975) as a tool in the statistical analysis of life data. The aging properties IFR, IFRA, NBUE and DMRL can be translated to properties of ϕF(t). Guided by these properties of ϕF(t) we suggest some test statistics for testing exponentiality against IFR, IFRA, NBUE and DMRL, respectively. The IFR and IFRA tests are new; the NBUE and DMRL tests have already been proposed and stu- died by Hollander and Proschan (1975) . The exact and asymptotic distributions of the statistics are derived and the asymptotic efficiencies of the tests are studied. The power of some tests is estimated by simulation for some alternatives when the sample size is n = 10 or n = 20.
In this article, a family of trimodal distributions is presented. The distributional properties and some of the inferential aspects of this family of trimodal distributions are discussed. We propose a moment based estimator as well as a maximum likelihood estimator of the parameters. A numerical simulation is conducted to evaluate the finite sample performances of the proposed estimators. A real data example is analyzed for illustration.
Vännman has earlier studied a class of capability indices, containing the indices Cp, Cpk, Cpm, and Cpmk, when the tolerances are symmetric. We study the properties of this class when the tolerances are asymmetric and suggest a new enlargened class of indices. Under the assumption of normality an explicit form of the distribution of the new class of the estimated indices is provided. Numerical investigations are made to explore the behavior of the estimators of the indices for different values of the parameters. Based on the estimator a decision rule that can be used to determine whether the process can be considered capable or not is provided and suitable criteria for choosing an index from the family are suggested.
A class of capability indices, containing the indices Cp, Cpk, Cpm, and Cpmk, has earlier been defined by the author for the case of two-sided specification intervals. By varying the parameters of the class various indices with suitable properties can be obtained. Under the assumption of normality new and simplified expressions of the distribution and the moments of the class of the estimated indices are provided when the target value equals the mid-point of the specification interval. It is shown that the cumulative distribution function can be expressed using only the central χ2-distribution and the normal distribution, which increases the utility of the class of indices.
The distribution of the estimated mean of the nonstandard mixture of distributions that has a discrete probability mass at zero and a gamma distribution for positive values is derived. Furthermore, for the studied nonstandard mixture of distributions, the distribution of the standardized statistic (estimator - true mean)/standard deviation of estimator is derived. The results are used to study the accuracy of the confidence interval for the mean based on a large sample approximation. Quantiles for the standardized statistic are also calculated.