Some Tests For Seasonality In Time Series Data,
2016
Federal University of Technology, Owerri
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,
2016
Department of Statistics, H. L. Institute of Commerce, Ahmedabad University
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,
2016
Al al-Bayt University, Mafraq, Jordan
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,
2016
Hacettepe University, Ankara, Turkey
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,
2016
University of Kashmir, Jammu and Kashmir, India
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,
2016
University of South Florida
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,
2016
Indian School of Mines, Dhanbad, India
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,
2016
University of Petra, Amman, Jordan
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,
2016
Wayne State University
Rao-Lovric And The Triwizard Point Null Hypothesis Tournament,
2016
Wayne State University
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,
2016
Indian School of Mines, Dhanbad, India
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),
2016
Wayne State University
Vol. 15, No. 2 (Full Issue), Jmasm Editors
Journal of Modern Applied Statistical Methods
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An Improved Generalized Estimation Procedure Of Current Population Mean In Two-Occasion Successive Sampling,
2016
Indian School of Mines, Dhanbad, India
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,
2016
U.S. Department of Defense
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,
2016
Janssen Pharmaceutica NV, Beerse, Belgium
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,
2016
Athens University of Economics and Business (AUEB)
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,
2016
University of Ibadan, Ibadan, Nigeria
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.
Monte Carlo Simulation Design For Evaluating Normal-Based Control Chart Properties,
2016
Georgia Southern University
Monte Carlo Simulation Design For Evaluating Normal-Based Control Chart Properties, John N. Dyer
Journal of Modern Applied Statistical Methods
The advent of more complicated control charting schemes has necessitated the use of Monte Carlo simulation (MCS) methods. Unfortunately, few sources exist to study effective design and validation of MCS methods related to control charting. This paper describes the design, issues, considerations and limitations for conducting normal-based control chart MCS studies, including choice of random number generator, simulation size requirements, and accuracy/error in simulation estimation. This paper also describes two design strategies for MCS for control chart evaluations and provides the programming code. As a result, this paper hopes to establish de facto MCS schemes aimed at guiding researchers and …
Latent Variable Model For Weight Gain Prevention Data With Informative Intermittent Missingness,
2016
Yale University
Latent Variable Model For Weight Gain Prevention Data With Informative Intermittent Missingness, Li Qin, Lisa Weissfeld, Michele Levine, Marsha Marcus, Feng Dai
Journal of Modern Applied Statistical Methods
Missing data is a common problem in longitudinal studies because of the characteristics of repeated measurements. Herein is proposed a latent variable model for nonignorable intermittent missing data in which the latent variables are used as random effects in modeling and link longitudinal responses and missingness process. In this methodology, the latent variables are assumed to be normally distributed with zero-mean, and the values of variance-covariance are calculated through maximum likelihood estimations. Parameter estimates and standard errors of the proposed method are compared with the mixed model and the complete-case analysis in the simulations and the application to the weight …
E-Bayesian Estimation Of The Parameter Of The Logarithmic Series Distribution,
2016
University of Payam Noor, Tehran, Iran
E-Bayesian Estimation Of The Parameter Of The Logarithmic Series Distribution, Parviz Nasiri, Hassan Esfandyarifar
Journal of Modern Applied Statistical Methods
E-Bayesian estimation is introduced to estimate the parameter of logarithmic series distribution. In addition, E-Bayesian, Bayesian and maximum likelihood estimation with through applying mean squared error.
