Results 21 to 30 of about 24,707 (163)

Confidence intervals for the common coefficient of variation of rainfall in Thailand [PDF]

PeerJ, 2020
The log-normal distribution is often used to analyze environmental data like daily rainfall amounts. The rainfall is of interest in Thailand because high variable climates can lead to periodic water stress and scarcity.
Warisa Thangjai, Sa-Aat Niwitpong, Suparat Niwitpong   +2 more
doaj   +2 more sources

Confidence Interval Estimation for the Common Mean of Several Zero-Inflated Gamma Distributions

Symmetry, 2022
In this study, we propose estimates for the confidence interval for the common mean of several zero-inflated gamma (ZIG) distributions based on the fiducial generalized confidence interval (GCI) and Bayesian and highest posterior density (HPD) methods ...
Theerapong Kaewprasert, S. Niwitpong, S. Niwitpong   +2 more
semanticscholar   +1 more source

Measuring the dispersion of rainfall using Bayesian confidence intervals for coefficient of variation of delta-lognormal distribution: a study from Thailand [PDF]

PeerJ, 2019
Since rainfall data series often contain zero values and thus follow a delta-lognormal distribution, the coefficient of variation is often used to illustrate the dispersion of rainfall in a number of areas and so is an important tool in statistical ...
Noppadon Yosboonruang, Sa-aat Niwitpong, Suparat Niwitpong   +2 more
doaj   +2 more sources

Confidence Intervals Based on the Difference of Medians for Independent Log-Normal Distributions

Mathematics, 2022
In this paper, we study the inferences of the difference of medians for two independent log-normal distributions. These methods include traditional methods such as the parametric bootstrap approach, the normal approximation approach, the method of ...
Weizhong Tian, Yaoting Yang, Tingting Tong   +2 more
doaj   +1 more source

Nonparametric generalized fiducial inference for survival functions under censoring [PDF]

Biometrika, 2017
Since the introduction of fiducial inference by Fisher in the 1930s, its application has been largely confined to relatively simple, parametric problems.
Yifan Cui, Jan Hannig
semanticscholar   +1 more source

Nonparametric generalized fiducial inference for survival functions under censoring [PDF]

, 2018
Fiducial Inference, introduced by Fisher in the 1930s, has a long history, which at times aroused passionate disagreements. However, its application has been largely confined to relatively simple parametric problems.
Cui, Yifan, Hannig, Jan
core   +3 more sources

Coherent frequentism [PDF]

, 2009
By representing the range of fair betting odds according to a pair of confidence set estimators, dual probability measures on parameter space called frequentist posteriors secure the coherence of subjective inference without any prior distribution.
Datta G. S., David R. Bickel, Fisher R. A., Fisher R. A., Gleser L. J., Hacking I., Hannig J., Kaplan M., Kyburg H. E. J., Molchanov I., Paris J. B., Pawitan Y., Smith C. A. B., Walley P., Welch B. L., Wilkinson G. N., Williamson J.   +16 more
core   +1 more source

Plausibility functions and exact frequentist inference [PDF]

, 2014
In the frequentist program, inferential methods with exact control on error rates are a primary focus. The standard approach, however, is to rely on asymptotic approximations, which may not be suitable.
Barndorff-Nielsen O.E., Bickel P.J., Bickel P.J., Bowman K.O., Eaton M.L., Fisher R.A., Garthwaite P.H., Ghosh J.K., Hannig J., Hotelling H., Lindley D.V., Liu C., Martin R., Ryan Martin, Shafer G., Spjøtvoll E., Varin C., Zhang T., ———, ———, ———, ———   +21 more
core   +1 more source

Conditional fiducial models [PDF]

, 2017
The fiducial is not unique in general, but we prove that in a restricted class of models it is uniquely determined by the sampling distribution of the data. It depends in particular not on the choice of a data generating model.
Lindqvist, Bo H., Taraldsen, Gunnar
core   +2 more sources

Inferential models: A framework for prior-free posterior probabilistic inference [PDF]

, 2013
Posterior probabilistic statistical inference without priors is an important but so far elusive goal. Fisher's fiducial inference, Dempster-Shafer theory of belief functions, and Bayesian inference with default priors are attempts to achieve this goal ...
Berger J., Berger J. O., Bernardo J.-M., Brown L. D., Cai T. T., Chuanhai Liu, Dawid A. P., Dawid A. P., Dempster A. P., Dempster A. P., Ermini Leaf D., Fraser D. A. S., Fraser D. A. S., Fraser D. A. S., Ghosh M., Hannig J., Hannig J., Hannig J., Heath D., Lehmann E. L., Little R., Martin R., Rubin D. B., Ryan Martin, Shafer G., Walley P., Wasserman L. A., Xie M., Zabell S. L., Zhang J.   +29 more
core   +1 more source