Monte Carlo Methods In Bayesian Inference: Theory, Methods And Applications,
2016
University of Arkansas, Fayetteville
Monte Carlo Methods In Bayesian Inference: Theory, Methods And Applications, Huarui Zhang
Graduate Theses and Dissertations
Monte Carlo methods are becoming more and more popular in statistics due to the fast development of efficient computing technologies. One of the major beneficiaries of this advent is the field of Bayesian inference. The aim of this thesis is two-fold: (i) to explain the theory justifying the validity of the simulation-based schemes in a Bayesian setting (why they should work) and (ii) to apply them in several different types of data analysis that a statistician has to routinely encounter. In Chapter 1, I introduce key concepts in Bayesian statistics. Then we discuss Monte Carlo Simulation methods in detail. Our …
Longitudinal Stability Of Effect Sizes In Education Research,
2016
Cleveland State University
Longitudinal Stability Of Effect Sizes In Education Research, Joshua Stephens
Journal of Modern Applied Statistical Methods
Educators use meta-analyses to decide best practices. It has been suggested that effect sizes have declined over time due to various biases. This study applies an established methodological framework to educational meta-analyses and finds that effect sizes have increased from 1970–present. Potential causes for this phenomenon are discussed.
The Application Of Legendre Multiwavelet Functions In Image Compression,
2016
Department of Mathematics, Karaj Branch, Islamic Azad University, Karaj, Iran
The Application Of Legendre Multiwavelet Functions In Image Compression, Elham Hashemizadeh, Sohrab Rahbar
Journal of Modern Applied Statistical Methods
Legendre multiwavelets are introduced. These functions can be designed in such a way that the properties of orthogonality, polynomial approximation, and symmetry hold at the same time. In this way, they can be effectively deployed in image compression.
Fitting Flexible Parametric Regression Models With Gldreg In R,
2016
Covance
Fitting Flexible Parametric Regression Models With Gldreg In R, Steve Su
Journal of Modern Applied Statistical Methods
This article outlines the functionality of the GLDreg package in R which fits parametric regression models using generalized lambda distributions via maximum likelihood estimation and L moment matching. The main advantage of GLDreg is the provision of robust regression lines and smooth regression quantiles beyond the capabilities of existing known methods.
Doubly Censored Data From Two-Component Mixture Of Inverse Weibull Distributions: Theory And Applications,
2016
Government Post Graduate College Muzaffarabad, Azad Kashmir, Pakistan
Doubly Censored Data From Two-Component Mixture Of Inverse Weibull Distributions: Theory And Applications, Tabassum Sindhu, Navid Feroze, Muhammad Aslam
Journal of Modern Applied Statistical Methods
Finite mixture distributions consist of a weighted sum of standard distributions and are a useful tool for reliability analysis of a heterogeneous population. They provide the necessary flexibility to model failure distributions of components with multiple failure models. The analysis of the mixture models under Bayesian framework has received sizable attention in the recent years. However, the Bayesian estimation of the mixture models under doubly censored samples has not yet been introduced in the literature. The main objective of this paper is to discuss the Bayes estimation of the inverse Weibull mixture distributions under doubly censoring. Different priors and loss …
Bayesian Analysis Of Discrete Skewed Laplace Distribution,
2016
Islamic Azad University, Marvdasht Branch, Marvdasht, Iran
Bayesian Analysis Of Discrete Skewed Laplace Distribution, A. Hossianzadeh, K Zare
Journal of Modern Applied Statistical Methods
The discrete skewed Laplace distribution is a flexible distribution with integer domain and simple closed form that can be applied to model count data. Parameters are estimated under empirical Bayes (EB) analysis and comparison are made between the Bayesian parameter estimation and classical parameter estimation, i.e. the maximum likelihood (ML) approach. The results show that the Bayesian parameter estimations are preferable.
A Comparison Of Usual T-Test Statistic And Modified T-Test Statistics On Skewed Distribution Functions,
2016
William Paterson University of New Jersey
A Comparison Of Usual T-Test Statistic And Modified T-Test Statistics On Skewed Distribution Functions, Wooi K. Lim, Alice W. Lim
Journal of Modern Applied Statistical Methods
When the sample size n is small, the random variable T= √n(\overline{X} – μ)/S is said to follow a central t distribution with degrees of freedom (n – 1), where \overline{X} is the sample mean and S is the sample standard deviation, provided that the data X ~ N (μ, σ2). The random variable T can be used as a test statistic to hypothesize the population mean μ. Some argue that the t-test statistic is robust against the normality of the distribution and claim that the normality assumption is not necessary. In this …
Designing Of Bayesian Skip Lot Sampling Plan Under Destructive Testing,
2016
Bharathiar University, Tamil Nadu, India
Designing Of Bayesian Skip Lot Sampling Plan Under Destructive Testing, K. K. Suresh, S. Umamaheswari
Journal of Modern Applied Statistical Methods
Skip-lot sampling plan serves as a cost-effective technique to manage the cost of performing frequent product inspections. As a powerful tool within a real-time quality management system, the ability to collect data which an optimize skip-lot sampling parameters affords manufacturers the luxury of lowering inspection expenses in various manufacturing units. The good quality of product can be produced in continuous improvement of production process in excellent quality history for suppliers. The procedures and necessary tables are provided for finding the respective plans for which sum of producer and consumer risks are minimized with acceptable and limiting quality levels which accounts …
Bayesian Inference For Median Of The Lognormal Distribution,
2016
SDM Degree College, Ujire, India
Bayesian Inference For Median Of The Lognormal Distribution, K. Aruna Rao, Juliet Gratia D'Cunha
Journal of Modern Applied Statistical Methods
Lognormal distribution has many applications. The past research papers concentrated on the estimation of the mean of this distribution. This paper develops credible interval for the median of the lognormal distribution. The estimated coverage probability and average length of the credible interval is compared with the confidence interval using Monte Carlo simulation.
The Br2 – Weighting Method For Estimating The Effects Of Air Pollution On Population Health,
2016
Fraser Health Authority, New Westminster, BC
The Br2 – Weighting Method For Estimating The Effects Of Air Pollution On Population Health, Goran Krstic, Nikolas S. Krstic, Mauricio Zambrano-Bigiarini
Journal of Modern Applied Statistical Methods
Uncertainties, limitations and biases may impede the correct application of concentration-response linear functions to estimate the effects of air pollution exposure on population health. The reliability of a prediction depends largely on the strength of the linear correlation between the studied variables. This work proposes the joint use of the coefficient of determination, r2, with the regression slope, b, as an improved measure of the strength of the linear relation between air pollution and its effects on population health. The proposed br2‑weighting method offers more reliable inferences about the potential effects of air pollution on …
Estimating The Parameter Of Exponential Distribution Under Type Ii Censoring From Fuzzy Data,
2016
Payame Noor University, Tehran, Iran
Estimating The Parameter Of Exponential Distribution Under Type Ii Censoring From Fuzzy Data, Iman Makhdoom, Parviz Nasiri, Abbas Pak
Journal of Modern Applied Statistical Methods
The problem of estimating the parameter of Exponential distribution on the basis of type II censoring scheme is considered when the available data are in the form of fuzzy numbers. The Bayes estimate of the unknown parameter is obtained by using the approximation forms of Lindley (1980) and Tierney and Kadane (1986) under the assumption of gamma prior. The highest posterior density (HPD) estimate of the parameter of interest is found. A Monte Carlo simulation is used to compare the performances of the different methods. A real data set is investigated to illustrate the applicability of …
Preliminary Tests Of Normality When Comparing Three Independent Samples,
2016
Chalmers University of Technology
Preliminary Tests Of Normality When Comparing Three Independent Samples, Björn Lantz, Roy Andersson, Peter Manfredsson
Journal of Modern Applied Statistical Methods
This paper uses simulation to explore the performance of a two-stage procedure where a preliminary Shapiro-Wilk test is used to choose between the ANOVA and Kruskal-Wallis tests as a three-sample location test. The results suggest that the two-stage procedure actually seems to be preferable when conducting such location tests.
Limited Failure Censored Life Test Sampling Plan In Burr Type X Distribution,
2016
Acharya Nagarjuna University, Guntur, Andhra Pradesh, India
Limited Failure Censored Life Test Sampling Plan In Burr Type X Distribution, R. R. L. Kantam, M. S. Ravikumar
Journal of Modern Applied Statistical Methods
The Burr type X distribution is considered as a life time random variable of a product whose lots are to be decided for acceptance or otherwise on the basis of sample lifetimes drawn from the lot. The sample is divided into various groups in order to develop a group sampling plan in such a way that the life testing experiment is terminated as soon as the first failure in each group is observed. The acceptance criterion based on the theory of order statistics is proposed and is shown to be more economical than a criterion proposed in the earlier similar …
Comparison Of Some Multivariate Nonparametric Tests In Profile Analysis To Repeated Measurements,
2016
Shiraz University of Medical Sciences, Shiraz, Iran
Comparison Of Some Multivariate Nonparametric Tests In Profile Analysis To Repeated Measurements, Mehrdad Vossoughi, Shila Shahvali, Erfan Sadeghi
Journal of Modern Applied Statistical Methods
Through Monte Carlo simulations, the performance of six multivariate nonparametric tests for testing the hypothesis of parallelism in profile analysis was studied. In conclusion, the tests based on ranks were as efficient as Hotelling's T2 under multivariate normal distribution. For the heavy tailed distribution, the tests based on signs performed best.
On Generalizing Cumulative Ordered Regression Models,
2016
Atkinson Graduate School of Management, Willamette University
On Generalizing Cumulative Ordered Regression Models, Robert W. Walker
Journal of Modern Applied Statistical Methods
We examine models that relax proportionality in cumulative ordered regression models. Something fundamental arising from ordered variables and stochastic ordering implies a partitioning. Efforts to relax proportionality also relax the ability to collapse an inherently multidimensional problem to a partitioning of the (unidimensional) real line. It is surprising and unfortunate to find that deviations from proportionality are sufficient to generate internal contradictions; undecidable propositions must exist by relaxing proportional odds without other relevant and significant changes in the underlying model. We prove a single theorem linking continuous support and partitions of a latent space to show that for these two …
Within Groups Anova When Using A Robust Multivariate Measure Of Location,
2016
University of Southern California
Within Groups Anova When Using A Robust Multivariate Measure Of Location, Rand Wilcox, Timothy Hayes
Journal of Modern Applied Statistical Methods
For robust measures of location associated with J dependent groups, various methods have been proposed that are aimed at testing the global hypothesis of a common measure of location applied to the marginal distributions. A criticism of these methods is that they do not deal with outliers in a manner that takes into account the overall structure of the data. Location estimators have been derived that deal with outliers in this manner, but evidently there are no simulation results regarding how well they perform when the goal is to test the some global hypothesis. The paper compares four bootstrap methods …
End Matter,
2016
Wayne State University
Some Remarks On Rao And Lovric’S ‘Testing Point Null Hypothesis Of A Normal Mean And The Truth: 21st Century Perspective’,
2016
University of British Columbia
Some Remarks On Rao And Lovric’S ‘Testing Point Null Hypothesis Of A Normal Mean And The Truth: 21st Century Perspective’, Bruno D. Zumbo, Edward Kroc
Journal of Modern Applied Statistical Methods
Although we have much to agree with in Rao and Lovric’s important discussion of the test of point null hypotheses, it stirred us to provide a way out of their apparent Zero probability paradox and cast the Hodges-Lehmann paradigm from a Serlin-Lapsley approach. We close our remarks with an eye toward a broad perspective.
Testing Point Null Hypothesis Of A Normal Mean And The Truth: 21st Century Perspective,
2016
Penn State University
Testing Point Null Hypothesis Of A Normal Mean And The Truth: 21st Century Perspective, Calyampudi Radhakrishna Rao, Miodrag M. Lovric
Journal of Modern Applied Statistical Methods
Testing a point (sharp) null hypothesis is arguably the most widely used statistical inferential procedure in many fields of scientific research, nevertheless, the most controversial, and misapprehended. Since 1935 when Buchanan-Wollaston raised the first criticism against hypothesis testing, this foundational field of statistics has drawn increasingly active and stronger opposition, including draconian suggestions that statistical significance testing should be abandoned or even banned. Statisticians should stop ignoring these accumulated and significant anomalies within the current point-null hypotheses paradigm and rebuild healthy foundations of statistical science. The foundation for a paradigm shift in testing statistical hypotheses is suggested, which is testing …
Study Of The Left Censored Data From The Gumbel Type Ii Distribution Under A Bayesian Approach,
2016
Quaid-i-Azam University, Islamabad, Pakistan
Study Of The Left Censored Data From The Gumbel Type Ii Distribution Under A Bayesian Approach, Tabassum Naz Sindhu, Navid Feroze, Muhammad Aslam
Journal of Modern Applied Statistical Methods
Based on left type II censored samples from a Gumbel type II distribution, the Bayes estimators and corresponding risks of the unknown parameter were obtained under different asymmetric loss functions, assuming different informative and non-informative priors. Elicitation of hyper-parameters through prior predictive approach has also been discussed. The expressions for the credible intervals and posterior predictive distributions have been derived. Comparisons of these estimators are made through simulation study using numerical and graphical methods.
