Determination of the Confidence Intervals for Multimodal Probability Density Functions

Determination of the Confidence Intervals for Multimodal Probability Density Functions

The shortest interval approach can be solved as an optimization problem, while the equallytailed approach is determined by using the distribution function. The equal density approach isproposed instead of the optimization problem for determining the shortest confidence interval. Itis applied to multimodal probability density functions to determine the shortest confidenceinterval. Furthermore, the equal density and optimization approach for the shortest confidenceinterval and the equally tailed approach were applied to numerical examples and their resultswere compared. Nevertheless, the main subject of this study is the calculation of the shortestconfidence intervals for any multimodal distribution.

___

  • Neyman, J., "Outline of a theory of statistical estimation based on the classical theory of probability", Philosophical Transactions of the Royal Society of London. Series A, Mathematical and Physical Sciences, 236(767): 333-380, (1937).
  • Wald, A., "Asymptotically shortest confidence intervals", The Annals of Mathematical Statistics, 13(2): 127-137, (1942).
  • Blyth, C.R., Hutchinson D.W., "Table of Neyman-shortest unbiased confidence intervals for the binomial parameter", Biometrika, 47(3/4): 381-391, (1960).
  • Sidak, Z., "Rectangular confidence regions for the means of multivariate normal distributions", Journal of the American Statistical Association, 62(318): 626-633, (1967).
  • Levy K., Narula, S., "Shortest confidence intervals for the ratio of two normal variances", Canadian Journal of Statistics, 2(1-2): 83-87, (1974).
  • DiCiccio, T.J., Romano, J.P., "A review of bootstrap confidence intervals", Journal of the Royal Statistical Society Series B Methodological, 338-354, (1988).
  • Owen, A.B., "Empirical likelihood ratio confidence intervals for a single functional", Biometrika, 75(2): 237-249, (1988).
  • Ferentinos, K.K, "Shortest confidence intervals for families of distributions involving truncation parameters", The American Statistician, 44(2): 167-168, (1990).
  • Ferentinos, K., Kourouklis, S., "Shortest confidence interval estimation for families of distributions involving two truncation parameters", Metrika, 37(1): 353-363, (1990).
  • Juola, R., "More on shortest confidence intervals", The American Statistician, 47(2): 117-119, (1993).
  • Weerahandi, S., "Generalized confidence intervals", In: Exact Statistical Methods for Data Analysis, Springer Series in Statistics, New York, 143-168, (1995).
  • Newcombe, R.G., "Two-sided confidence intervals for the single proportion: comparison of seven methods", Statistics in Medicine, 17(8): 857-872, (1998).
  • Willink, R. "A confidence interval and test for the mean of an asymmetric distribution", Communications in Statistics—Theory and Methods, 34(4): 753-766, (2005).
  • Zhou, X.H., Dinh, P., "Nonparametric confidence intervals for the one-and two-sample problems", Biostatistics, 6(2): 187-200, (2005).
  • Kibria, G.B., "Modified confidence intervals for the mean of the asymmetric distribution", Pakistan Journal of Statistics, 22(2): 109-120, (2006).
  • Burch, B.D., "Comparing equal-tail probability and unbiased confidence intervals for the intraclass correlation coefficient", Communications in Statistics—Theory and Methods, 37(20): 3264-3275, (2008).
  • Evans, M., Shakhatreh, M., "Optimal properties of some Bayesian inferences", Electronic Journal of Statistics, 2: 1268-1280, (2008).
  • Baklizi, A., Kibria, B.G., "One and two sample confidence intervals for estimating the mean of skewed populations: an empirical comparative study", Journal of Applied Statistics, 36(6): 601-609, (2009).
  • Banik, S., Kibria, B.G., "Comparison of some parametric and nonparametric type one sample confidence intervals for estimating the mean of a positively skewed distribution", Communications in Statistics—Simulation and Computation, 39(2): 361-389, (2010).
  • Banik S., Kibria, B.G., "Estimating the population coefficient of variation by confidence intervals", Communications in Statistics-Simulation and Computation, 40(8): 1236-1261, (2011).
  • Gulhar, M., Kibria, G.K., Albatineh, A.N., Ahmed, N.U., "A comparison of some confidence intervals for estimating the population coefficient of variation: a simulation study", SORT: Statistics and Operations Research Transactions, 36(1): 45-68, (2012).
  • Alizadeh, M., Parchami, A., Mashinchi, M., "Unbiased confidence intervals for distributions involving truncation parameter", In: ProbStat Forum, (2013).
  • Mammen, E., Polonik, W., "Confidence regions for level sets", Journal of Multivariate Analysis, 122: 202-214, (2013).
  • Fagerland, M.W., Lydersen, S., Laake, P., "Recommended confidence intervals for two independent binomial proportions", Statistical Methods in Medical Research, 24(2): 224-254, (2015).
  • Pratt, J.W., "Length of confidence intervals", Journal of the American Statistical Association, 56(295): 549-567, (1961).
  • Casella, G., Berger, R.L., Statistical inference 2 nd ed, Duxbury/Thomson Learning, (2001).
  • Smithson, M., “Confidence intervals”, Sage Publications, 140, (2002).
  • Guenther, W.C., "Unbiased confidence intervals", The American Statistician, 25(1): 51-53, (1971).
  • Stoer J., Bulirsch, R., Introduction to numerical analysis, Springer, Science & Business Media, 12, (2013).
  • Tate, R.F., Klett, G.W., "Optimal confidence intervals for the variance of a normal distribution", Journal of the American Statistical Association, 54(287): 674-682, (1959).
  • Guenther, W.C., "Shortest confidence intervals", The American Statistician, 23(1): 22-25, (1969).
  • Gao, S., Zhang, Z., Cao, C., "Particle swarm optimization algorithm for the shortest confidence interval problem", Journal of Computers, 7(8): 1809-1816, (2012).
  • Roussas, G.G., A Course in Mathematical Statistics, Academic Press, (1997).