Open Access. Powered by Scholars. Published by Universities.®

Statistical Theory Commons™

Open Access. Powered by Scholars. Published by Universities.®

Applied Statistics

Institution
Keyword
Publication Year
Publication
Publication Type

Articles 301 - 330 of 1191

Full-Text Articles in Statistical Theory

Designing Of Bayesian Skip Lot Sampling Plan Under Destructive Testing, K. K. Suresh, S. Umamaheswari Nov 2016

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, K. Aruna Rao, Juliet Gratia D'Cunha Nov 2016

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, Goran Krstic, Nikolas S. Krstic, Mauricio Zambrano-Bigiarini Nov 2016

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, Iman Makhdoom, Parviz Nasiri, Abbas Pak Nov 2016

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, Björn Lantz, Roy Andersson, Peter Manfredsson Nov 2016

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, R. R. L. Kantam, M. S. Ravikumar Nov 2016

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, Mehrdad Vossoughi, Shila Shahvali, Erfan Sadeghi Nov 2016

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, Robert W. Walker Nov 2016

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, Rand Wilcox, Timothy Hayes Nov 2016

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, Jmasm Editors Nov 2016

End Matter, Jmasm Editors

Journal of Modern Applied Statistical Methods

.


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 Nov 2016

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, Calyampudi Radhakrishna Rao, Miodrag M. Lovric Nov 2016

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, Tabassum Naz Sindhu, Navid Feroze, Muhammad Aslam Nov 2016

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.


Some Tests For Seasonality In Time Series Data, Eleazar Chukwunenye Nwogu, Iheanyi Sylvester Iwueze, Valentine Uchenna Nlebedim Nov 2016

Some Tests For Seasonality In Time Series Data, Eleazar Chukwunenye Nwogu, Iheanyi Sylvester Iwueze, Valentine Uchenna Nlebedim

Journal of Modern Applied Statistical Methods

This paper presents some tests for seasonality in a time series data which considers the model structure and the nature of trending curve. The tests were applied to the row variances of the Buys Ballot table. The student t-test and Wilcoxon Signed-Ranks test have been recommended for detection of seasonality.


Hierarchical Bayes Estimation Of Reliability Indexes Of Cold Standby Series System Under General Progressive Type Ii Censoring Scheme, D. R. Barot, M. N. Patel Nov 2016

Hierarchical Bayes Estimation Of Reliability Indexes Of Cold Standby Series System Under General Progressive Type Ii Censoring Scheme, D. R. Barot, M. N. Patel

Journal of Modern Applied Statistical Methods

In this paper, hierarchical Bayes approach is presented for estimation and prediction of reliability indexes and remaining lifetimes of a cold standby series system under general progressive Type II censoring scheme. A simulation study has been carried out for comparison purpose. The study will help reliability engineers in various industrial series system setups.


A New Estimator Of The Population Mean: An Application To Bioleaching Studies, Amer I. Al-Omari, Carlos N. Bouza, Dante Covarrubias, Roma Pal Nov 2016

A New Estimator Of The Population Mean: An Application To Bioleaching Studies, Amer I. Al-Omari, Carlos N. Bouza, Dante Covarrubias, Roma Pal

Journal of Modern Applied Statistical Methods

The multistage balanced groups ranked set samples (MBGRSS) method is considered for estimating the population mean for samples of size m = 3k where k is a positive real integer. It is compared with the simple random sampling (SRS) and ranked set sampling (RSS) schemes. For the symmetric distributions considered in this study, the MBGRSS estimator is an unbiased estimator of the population mean and it is more efficient than SRS and RSS methods based on the same number of measured units. Its efficiency is increasing in s for fixed value of the sample size, where s is the …


A New Exponential Type Estimator For The Population Mean In Simple Random Sampling, Gamze Özel Kadilar Nov 2016

A New Exponential Type Estimator For The Population Mean In Simple Random Sampling, Gamze Özel Kadilar

Journal of Modern Applied Statistical Methods

This paper provides a new exponential type estimator in simple random sampling for population mean. It is shown that proposed exponential type estimator is always more efficient than estimators considered by Bahl and Tuteja (1991) and Singh, Chauhan, Sawan, and Smarandache (2009). From numerical examples it is also observed that proposed modified ratio estimator performs better than existing estimators.


Bayesian Analysis Of Generalized Exponential Distribution, Saima Naqash, S. P. Ahmad, Aquil Ahmed Nov 2016

Bayesian Analysis Of Generalized Exponential Distribution, Saima Naqash, S. P. Ahmad, Aquil Ahmed

Journal of Modern Applied Statistical Methods

Bayesian estimators of unknown parameters of a two parameter generalized exponential distribution are obtained based on non-informative priors using different loss functions.


Regularized Neural Network To Identify Potential Breast Cancer: A Bayesian Approach, Hansapani S. Rodrigo, Chris P. Tsokos, Taysseer Sharaf Nov 2016

Regularized Neural Network To Identify Potential Breast Cancer: A Bayesian Approach, Hansapani S. Rodrigo, Chris P. Tsokos, Taysseer Sharaf

Journal of Modern Applied Statistical Methods

In the current study, we have exemplified the use of Bayesian neural networks for breast cancer classification using the evidence procedure. The optimal Bayesian network has 81% overall accuracy in correctly classifying the true status of breast cancer patients, 59% sensitivity in correctly detecting the malignancy and 83% specificity in correctly detecting the non-malignancy. The area under the receiver operating characteristic curve (0.7940) shows that this is a moderate classification model.


Efficient And Unbiased Estimation Procedure Of Population Mean In Two-Phase Sampling, Reba Maji, Arnab Bandyopadhyay, G. N. Singh Nov 2016

Efficient And Unbiased Estimation Procedure Of Population Mean In Two-Phase Sampling, Reba Maji, Arnab Bandyopadhyay, G. N. Singh

Journal of Modern Applied Statistical Methods

In this paper, an unbiased regression-ratio type estimator has been developed for estimating the population mean using two auxiliary variables in double sampling. Its properties are studied under two different cases. Empirical studies and graphical simulation have been done to demonstrate the efficiency of the proposed estimator over other estimators.


A Generalization Of The Weibull Distribution With Applications, Maalee Almheidat, Carl Lee, Felix Famoye Nov 2016

A Generalization Of The Weibull Distribution With Applications, Maalee Almheidat, Carl Lee, Felix Famoye

Journal of Modern Applied Statistical Methods

The Lomax-Weibull distribution, a generalization of the Weibull distribution, is characterized by four parameters that describe the shape and scale properties. The distribution is found to be unimodal or bimodal and it can be skewed to the right or left. Results for the non-central moments, limiting behavior, mean deviations, quantile function, and the mode(s) are obtained. The relationships between the parameters and the mean, variance, skewness, and kurtosis are provided. The method of maximum likelihood is proposed for estimating the distribution parameters. The applicability of this distribution to modeling real life data is illustrated by three examples and the results …


Front Matter, Jmasm Editors Nov 2016

Front Matter, Jmasm Editors

Journal of Modern Applied Statistical Methods

.


Rao-Lovric And The Triwizard Point Null Hypothesis Tournament, Shlomo Sawilowsky Nov 2016

Rao-Lovric And The Triwizard Point Null Hypothesis Tournament, Shlomo Sawilowsky

Journal of Modern Applied Statistical Methods

The debate if the point null hypothesis is ever literally true cannot be resolved, because there are three competing statistical systems claiming ownership of the construct. The local resolution depends on personal acclimatization to a Fisherian, Frequentist, or Bayesian orientation (or an unexpected fourth champion if decision theory is allowed to compete). Implications of Rao and Lovric’s proposed Hodges-Lehman paradigm are discussed in the Appendix.


Estimation Of Population Mean On Recent Occasion Under Non-Response In H-Occasion Successive Sampling, Anup Kumar Sharma, Garib Nath Singh Nov 2016

Estimation Of Population Mean On Recent Occasion Under Non-Response In H-Occasion Successive Sampling, Anup Kumar Sharma, Garib Nath Singh

Journal of Modern Applied Statistical Methods

In this article, an attempt has been made to study on general estimation procedures of population mean on recent occasion when non-response occurs in h-occasion successive sampling. Suggested estimators have advantageously influenced the estimation procedures in the presence of non-response. Detailed properties of the suggested estimation procedures have been examined and compared with the estimation process of the same circumstances but in the absence of non-response. Empirical studies have been carried out to demonstrate the performances of the estimates and suitable recommendations have been made.


Vol. 15, No. 2 (Full Issue), Jmasm Editors Nov 2016

Vol. 15, No. 2 (Full Issue), Jmasm Editors

Journal of Modern Applied Statistical Methods

.


An Improved Generalized Estimation Procedure Of Current Population Mean In Two-Occasion Successive Sampling, G. N. Singh, Alok Kumar Singh, Anup Kumar Sharma Nov 2016

An Improved Generalized Estimation Procedure Of Current Population Mean In Two-Occasion Successive Sampling, G. N. Singh, Alok Kumar Singh, Anup Kumar Sharma

Journal of Modern Applied Statistical Methods

The present work is an attempt to make use of several auxiliary variables on both occasions for improving the precision of estimates for the current population mean in two-occasion successive sampling. A generalized exponential-cum-regression type estimator of the current population mean is proposed and its optimum replacement strategy has been discussed. Empirical studies are carried out to show the dominance of the proposed estimation procedure over the sample mean estimator and natural successive sampling estimator. Empirical results have been interpreted and suitable recommendations are put forward to survey practitioners.


A Comprehensive Review Of The Two-Sample Independent Or Paired Binary Data, With Or Without Stratum Effects, Dewi Rahardja, Ying Yang, Zhiwei Zhang Nov 2016

A Comprehensive Review Of The Two-Sample Independent Or Paired Binary Data, With Or Without Stratum Effects, Dewi Rahardja, Ying Yang, Zhiwei Zhang

Journal of Modern Applied Statistical Methods

Various statistical hypotheses testing for discrete or categorical or binary data have been extensively discussed in the literature. A comprehensive review is given for the two-sample binary or categorical data testing methods on data with or without Stratum Effects. The review includes traditional methods such as Fisher’s Exact, Pearson’s Chi-Square, McNemar, Bowker, Stuart-Maxwell, Breslow-Day and, Cochran-Mantel-Haenszel, as well as newly developed ones. We also provide the roadmap, in a figure or diagram format to which methods are available in the literature. In addition, the implementation of these methods in popular statistical software packages such as SAS and/or R is also …


Evaluation Of The Addition Of Firth’S Penalty Term To The Bradley-Terry Likelihood, Paul Meyvisch Nov 2016

Evaluation Of The Addition Of Firth’S Penalty Term To The Bradley-Terry Likelihood, Paul Meyvisch

Journal of Modern Applied Statistical Methods

A major shortcoming of the Bradley-Terry model is that the maximum likelihood estimates are infinite-valued in the presence of separation and may be unreliable when data are nearly separated. A well-known solution consists of the addition of Firth' s penalty term to the log-likelihood function, and solve this penalized likelihood through logistic regression.The maximum likelihood estimates with and without Firth's penalty are compared in a large and heterogeneous population of table-tennis players. We additionally show that exact penalized maximum likelihood estimates can be reasonably approximated using a well-chosen Minorization-Maximization (MM) algorithm.


Optimal Estimation And Sampling Allocation In Survey Sampling Under A General Correlated Superpopulation Model, Ioulia Papageorgiou Nov 2016

Optimal Estimation And Sampling Allocation In Survey Sampling Under A General Correlated Superpopulation Model, Ioulia Papageorgiou

Journal of Modern Applied Statistical Methods

Sampling from a finite population with correlated units is addressed. The proposed methodology applies to any type of correlation function and provides the sample allocation that ensures optimal efficiency of the population parameters estimates. The expressions of the estimate and its MSE are also provided.


An Adjusted Network Information Criterion For Model Selection In Statistical Neural Network Models, Christopher Godwin Udomboso, Godwin Nwazu Amahia, Isaac Kwame Dontwi Nov 2016

An Adjusted Network Information Criterion For Model Selection In Statistical Neural Network Models, Christopher Godwin Udomboso, Godwin Nwazu Amahia, Isaac Kwame Dontwi

Journal of Modern Applied Statistical Methods

In this paper, we derived and investigated the Adjusted Network Information Criterion (ANIC) criterion, based on Kullback’s symmetric divergence, which has been designed to be an asymptotically unbiased estimator of the expected Kullback-Leibler information of a fitted model. The ANIC improves model selection in more sample sizes than does the NIC.