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Articles 1 - 30 of 102
Full-Text Articles in Physical Sciences and Mathematics
Unit Root Test For Panel Data Ar(1) Time Series Model With Linear Time Trend And Augmentation Term: A Bayesian Approach, Jitendra Kumar, Anoop Chaturvedi, Umme Afifa, Shafat Yousuf, Saurabh Kumar
Unit Root Test For Panel Data Ar(1) Time Series Model With Linear Time Trend And Augmentation Term: A Bayesian Approach, Jitendra Kumar, Anoop Chaturvedi, Umme Afifa, Shafat Yousuf, Saurabh Kumar
Journal of Modern Applied Statistical Methods
The univariate time series models, in the case of unit root hypothesis, are more biased towards the acceptance of the Unit Root Hypothesis especially in a short time span. However, the panel data time series model is more appropriate in such situation. The Bayesian analysis of unit root testing for a panel data time series model is considered. An autoregressive panel data AR(1) model with linear time trend and augmentation term has been considered and derived the posterior odds ratio for testing the presence of unit root hypothesis under appropriate prior assumptions. A simulation study and real data analysis are …
'Parallel Universe' Or 'Proven Future'? The Language Of Dependent Means T-Test Interpretations, Anthony M. Gould, Jean-Etienne Joullié
'Parallel Universe' Or 'Proven Future'? The Language Of Dependent Means T-Test Interpretations, Anthony M. Gould, Jean-Etienne Joullié
Journal of Modern Applied Statistical Methods
Of the three kinds of two-mean comparisons which judge a test statistic against a critical value taken from a Student t-distribution, one – the repeated measures or dependent-means application – is distinctive because it is meant to assess the value of a parameter which is not part of the natural order. This absence forces a choice between two interpretations of a significant test result and the meaning of the test hypothesis. The parallel universe view advances a conditional, backward-looking conclusion. The more practical proven future interpretation is a non-conditional proposition about what will happen if an intervention is (now) applied …
Proportional Reversed Hazard Rate Models With Exponential Baseline, G. Barmalzan, H. Saboori
Proportional Reversed Hazard Rate Models With Exponential Baseline, G. Barmalzan, H. Saboori
Applications and Applied Mathematics: An International Journal (AAM)
The proportional hazard regression models have been used extensively in survival analysis to understand and exploit the relationship between survival time and covariates. For left censored survival times, reversed hazard rate functions are more appropriate. In this paper, we discuss a parametric proportional reversed hazard rates model using exponential baseline. The estimation for the parameters are discussed. We also assess the performance of the proposed procedure based on a large number of Monte Carlo simulations. Finally, we illustrate the proposed method using a real case example and then we show that it provides a good and better fit than the …
Robust Measures Of Variable Importance For Multivariate Group Designs, Tolulope T. Sajobi, Lisa M. Lix
Robust Measures Of Variable Importance For Multivariate Group Designs, Tolulope T. Sajobi, Lisa M. Lix
Journal of Modern Applied Statistical Methods
Variable importance measures based on discriminant analysis and multivariate analysis of variance are useful for identifying variables that discriminate between two groups in multivariate group designs. Variable importance measures are developed based on trimmed and Winsorized estimators for describing group differences in multivariate non-normal populations.
Modeling Agreement Between Binary Classifications Of Multiple Raters In R And Sas, Aya A. Mitani, Kerrie P. Nelson
Modeling Agreement Between Binary Classifications Of Multiple Raters In R And Sas, Aya A. Mitani, Kerrie P. Nelson
Journal of Modern Applied Statistical Methods
Cancer screening and diagnostic tests often are classified using a binary outcome such as diseased or not diseased. Recently large-scale studies have been conducted to assess agreement between many raters. Measures of agreement using the class of generalized linear mixed models were implemented efficiently in four recently introduced R and SAS packages in large-scale agreement studies incorporating binary classifications. Simulation studies were conducted to compare the performance across the packages and apply the agreement methods to two cancer studies.
Inferential Procedures For Log Logistic Distribution With Doubly Interval Censored Data, Yue Fang Loh, Jayanthi Arasan, Habshah Midi, M. R. Abu Bakar
Inferential Procedures For Log Logistic Distribution With Doubly Interval Censored Data, Yue Fang Loh, Jayanthi Arasan, Habshah Midi, M. R. Abu Bakar
Journal of Modern Applied Statistical Methods
The log logistic model with doubly interval censored data is examined. Three methods of constructing confidence interval estimates for the parameter of the model were compared and discussed. The results of the coverage probability study indicated that the Wald outperformed the likelihood ratio and jackknife inferential procedures.
Approximating The Distribution Of Indefinite Quadratic Forms In Normal Variables By Maximum Entropy Density Estimation, Ghasem Rekabdar, Rahim Chinipardaz
Approximating The Distribution Of Indefinite Quadratic Forms In Normal Variables By Maximum Entropy Density Estimation, Ghasem Rekabdar, Rahim Chinipardaz
Journal of Modern Applied Statistical Methods
The quadratic form of non-central normal variables is presented based on a sum of weighted independent non-central chi-square variables. This presentation provides moments of quadratic form. The maximum entropy method is used to estimate the density function because distribution moments of quadratic forms are known. A Euclidean distance is proposed to select an appropriate maximum entropy density function. In order to compare with other methods some numerical examples were evaluated. Also, for discrimination between two groups by the Euclidean distances, we obtained a stochastic representation for the linear discriminant function using the quadratic form. The maximum entropy estimation was an …
Missing Data In Longitudinal Surveys: A Comparison Of Performance Of Modern Techniques, Paola Zaninotto, Amanda Sacker
Missing Data In Longitudinal Surveys: A Comparison Of Performance Of Modern Techniques, Paola Zaninotto, Amanda Sacker
Journal of Modern Applied Statistical Methods
Using a simulation study, the performance of complete case analysis, full information maximum likelihood, multivariate normal imputation, multiple imputation by chained equations and two-fold fully conditional specification to handle missing data were compared in longitudinal surveys with continuous and binary outcomes, missing covariates, and an interaction term.
Semi-Parametric Method To Estimate The Time-To-Failure Distribution And Its Percentiles For Simple Linear Degradation Model, Laila Naji Ba Dakhn, Mohammed Al-Haj Ebrahem, Omar Eidous
Semi-Parametric Method To Estimate The Time-To-Failure Distribution And Its Percentiles For Simple Linear Degradation Model, Laila Naji Ba Dakhn, Mohammed Al-Haj Ebrahem, Omar Eidous
Journal of Modern Applied Statistical Methods
Most reliability studies obtained reliability information by using degradation measurements over time, which contains useful data about the product reliability. Parametric methods like the maximum likelihood (ML) estimator and the ordinary least square (OLS) estimator are used widely to estimate the time-to-failure distribution and its percentiles. In this article, we estimate the time-to-failure distribution and its percentiles by using a semi-parametric estimator that assumes the parametric function to have a half- normal distribution or an exponential distribution. The performance of the semi-parametric estimator is compared via simulation study with the ML and OLS estimators by using the mean square error …
On Variance Balanced Designs, Dilip Kumar Ghosh, Sangeeta Ahuja
On Variance Balanced Designs, Dilip Kumar Ghosh, Sangeeta Ahuja
Journal of Modern Applied Statistical Methods
Balanced incomplete block designs are not always possible to construct because of their parametric relations. In such a situation another balanced design, the variance balanced design, is required. This construction of binary, equal replicated variance balanced designs are discussed using the half fraction of the 2n factorial designs with smaller block sizes. This method was also extended to construct another variance balanced design by deleting the last block of the resulting variance balanced designs. Its efficiency factor compared with randomized block designs was compared and found to be highly efficient.
Jmasm 48: The Pearson Product-Moment Correlation Coefficient And Adjustment Indices: The Fisher Approximate Unbiased Estimator And The Olkin-Pratt Adjustment (Spss), David A. Walker
Journal of Modern Applied Statistical Methods
This syntax program is intended to provide an application, not readily available, for users in SPSS who are interested in the Pearson product–moment correlation coefficient (r) and r biased adjustment indices such as the Fisher Approximate Unbiased estimator and the Olkin and Pratt adjustment.
On Poisson Quasi-Lindley Distribution And Its Applications, Razika Grine, Halim Zeghdoudi
On Poisson Quasi-Lindley Distribution And Its Applications, Razika Grine, Halim Zeghdoudi
Journal of Modern Applied Statistical Methods
This paper proposes a recent version of compound Poisson distributions named the Poisson quasi-Lindley (PQL) distribution by compounding Poisson and quasi-Lindley distributions. Some properties of the distributions are given with estimation and some illustrative examples.
Detection Of Outliers In Univariate Circular Data Using Robust Circular Distance, Ehab A. Mahmood, Sohel Rana, Habshah Midi, Abdul Ghapor Hussin
Detection Of Outliers In Univariate Circular Data Using Robust Circular Distance, Ehab A. Mahmood, Sohel Rana, Habshah Midi, Abdul Ghapor Hussin
Journal of Modern Applied Statistical Methods
A robust statistic to detect single and multi-outliers in univariate circular data is proposed. The performance of the proposed statistic was tested by applying it to a simulation study and to three real data sets, and was demonstrated to be robust.
Performance Evaluation Of Confidence Intervals For Ordinal Coefficient Alpha, Heather J. Turner, Prathiba Natesan, Robin K. Henson
Performance Evaluation Of Confidence Intervals For Ordinal Coefficient Alpha, Heather J. Turner, Prathiba Natesan, Robin K. Henson
Journal of Modern Applied Statistical Methods
The aim of this study was to investigate the performance of the Fisher, Feldt, Bonner, and Hakstian and Whalen (HW) confidence intervals methods for the non-parametric reliability estimate, ordinal alpha. All methods yielded unacceptably low coverage rates and potentially increased Type-I error rates.
Around Gamma Lindley Distribution, Hamouda Messaadia, Halim Zeghdoudi
Around Gamma Lindley Distribution, Hamouda Messaadia, Halim Zeghdoudi
Journal of Modern Applied Statistical Methods
Some remarks and correction on a new distribution, Gamma Lindley, of which the Lindley distribution is a particular case, are given pertaining to its parameter space.
Jmasm 49: A Compilation Of Some Popular Goodness Of Fit Tests For Normal Distribution: Their Algorithms And Matlab Codes (Matlab), Metin Öner, İpek Deveci Kocakoç
Jmasm 49: A Compilation Of Some Popular Goodness Of Fit Tests For Normal Distribution: Their Algorithms And Matlab Codes (Matlab), Metin Öner, İpek Deveci Kocakoç
Journal of Modern Applied Statistical Methods
The main purpose of this study is to review calculation algorithms for some of the most common non-parametric and omnibus tests for normality, and to provide them as a compiled MATLAB function. All tests are coded to provide p-values for those normality tests, and the proposed function gives the results as an output table.
Bayesian Hypothesis Testing Of Two Normal Samples Using Bootstrap Prior Technique, Oyebayo Ridwan Olaniran, Waheed Babatunde Yahya
Bayesian Hypothesis Testing Of Two Normal Samples Using Bootstrap Prior Technique, Oyebayo Ridwan Olaniran, Waheed Babatunde Yahya
Journal of Modern Applied Statistical Methods
The most important ingredient in Bayesian analysis is prior or prior distribution. A new prior determination method was developed under the framework of parametric empirical Bayes using bootstrap technique. By way of example, Bayesian estimations of the parameters of a normal distribution with unknown mean and unknown variance conditions were considered, as well as its application in comparing the means of two independent normal samples with several scenarios. A Monte Carlo study was conducted to illustrate the proposed procedure in estimation and hypothesis testing. Results from Monte Carlo studies showed that the bootstrap prior proposed is more efficient than the …
A Monte Carlo Study Of The Effects Of Variability And Outliers On The Linear Correlation Coefficient, Hussein Yousif Eledum
A Monte Carlo Study Of The Effects Of Variability And Outliers On The Linear Correlation Coefficient, Hussein Yousif Eledum
Journal of Modern Applied Statistical Methods
Monte Carlo simulations are used to investigate the effect of two factors, the amount of variability and an outlier, on the size of the Pearson correlation coefficient. Some simulation algorithms are developed, and two theorems for increasing or decreasing the amount of variability are suggested.
The Regression Smoother Lowess: A Confidence Band That Allows Heteroscedasticity And Has Some Specified Simultaneous Probability Coverage, Rand Wilcox
Journal of Modern Applied Statistical Methods
Many nonparametric regression estimators (smoothers) have been proposed that provide a more flexible method for estimating the true regression line compared to using some of the more obvious parametric models. A basic goal when using any smoother is computing a confidence band for the true regression line. Let M(Y|X) be some conditional measure of location associated with the random variable Y, given X and let x be some specific value of the covariate. When using the LOWESS estimator, an extant method that assumes homoscedasticity can be used to compute a confidence interval for M(Y|X = x). A trivial way of …
The Impact Of Predictor Variable(S) With Skewed Cell Probabilities On Wald Tests In Binary Logistic Regression, Arwa Alkhalaf, Bruno D. Zumbo
The Impact Of Predictor Variable(S) With Skewed Cell Probabilities On Wald Tests In Binary Logistic Regression, Arwa Alkhalaf, Bruno D. Zumbo
Journal of Modern Applied Statistical Methods
A series of simulation studies are reported that investigated the impact of a skewed predictor(s) on the Type I error rate and power of the Wald test in a logistic regression model. Five simulations were conducted for three different regression models. A detailed description of the impact of skewed cell predictor probabilities and sample size provide guidelines for practitioners wherein to expect the greatest problems.
Jmasm 47: Anova_Hov: A Sas Macro For Testing Homogeneity Of Variance In One-Factor Anova Models (Sas), Isaac Li, Yi-Hsin Chen, Yan Wang, Patricia RodríGuez De Gil, Thanh Pham, Diep Nguyen, Eun Sook Kim, Jeffrey D. Kromrey
Jmasm 47: Anova_Hov: A Sas Macro For Testing Homogeneity Of Variance In One-Factor Anova Models (Sas), Isaac Li, Yi-Hsin Chen, Yan Wang, Patricia RodríGuez De Gil, Thanh Pham, Diep Nguyen, Eun Sook Kim, Jeffrey D. Kromrey
Journal of Modern Applied Statistical Methods
Variance homogeneity (HOV) is a critical assumption for ANOVA whose violation may lead to perturbations in Type I error rates. Minimal consensus exists on selecting an appropriate test. This SAS macro implements 14 different HOV approaches in one-way ANOVA. Examples are given and practical issues discussed.
Jmasm 50: A Web-Based Shiny Application For Conducting A Two Dependent Samples Maximum Test (R), Saverpierre Maggio, Gokul Bhandari, Shlomo S. Sawilowsky
Jmasm 50: A Web-Based Shiny Application For Conducting A Two Dependent Samples Maximum Test (R), Saverpierre Maggio, Gokul Bhandari, Shlomo S. Sawilowsky
Journal of Modern Applied Statistical Methods
A web-based Shiny application written in R statistical language was developed and deployed online to calculate a new two dependent samples maximum test as presented in Maggio and Sawilowsky (2014b). The maximum test allows researchers to conduct both the dependent samples t-test and Wilcoxon signed-ranks tests on same data without raising concerns associated with Type I error inflation and choice of statistical tests (Maggio and Sawilowsky, 2014a). The maximum test in R statistical language provides a friendly user interface.
The Impact Of Inappropriate Modeling Of Cross-Classified Data Structures On Random-Slope Models, Feifei Ye, Laura Daniel
The Impact Of Inappropriate Modeling Of Cross-Classified Data Structures On Random-Slope Models, Feifei Ye, Laura Daniel
Journal of Modern Applied Statistical Methods
Previous studies that explored the impact of misspecification of cross-classified data structure as strictly hierarchical are limited to random intercept models. This study examined the effects of misspecification of a two-level, cross-classified, random effect model (CCREM) where both the level-1 intercept and slope were allowed to vary randomly. Results suggest that ignoring one of the crossed factors produced considerably underestimated standard errors for: 1) the regression coefficients of the level-1 predictor; 2) the inappropriately modeled predictor associated with the misspecified crossed factor; and 3) and their interaction. This misspecification also resulted in a significant inflation of the level-1 residual variances …
A Remark For The Admissibility Of Rao’S U-Test, Z. D. Bai, C. R. Rao, M. T. Tsai
A Remark For The Admissibility Of Rao’S U-Test, Z. D. Bai, C. R. Rao, M. T. Tsai
Journal of Modern Applied Statistical Methods
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Front Matter, Jmasm Editors
Vol. 16, No. 2 (Full Issue), Jmasm Editors
Vol. 16, No. 2 (Full Issue), Jmasm Editors
Journal of Modern Applied Statistical Methods
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Stationary Analysis Of A Multiserver Queue With Multiple Working Vacation And Impatient Customers, P. Manoharan, Shakir Majid
Stationary Analysis Of A Multiserver Queue With Multiple Working Vacation And Impatient Customers, P. Manoharan, Shakir Majid
Applications and Applied Mathematics: An International Journal (AAM)
We consider an M/M/c queue with multiple working vacation and impatient customers. The server serves the customers at a lower rate rather than completely halts the service during this working vacation period. The impatience of the customer’s arises when they arrive during the working vacation period, where the service rate of the customer’s is lower than the normal busy period. The queue is analyzed for multiple working vacation policies. The policy of a MWV demands the server to keep taking vacation until it finds at least a single customer waiting in the system at an instant vacation completion. On returning …
Transient Solution Of M[X1],M[X2]/G1,G2/1 With Priority Services, Modified Bernoulli Vacation, Bernoulli Feedback, Breakdown, Delaying Repair And Reneging, G. Ayyappan, J. Udayageetha
Transient Solution Of M[X1],M[X2]/G1,G2/1 With Priority Services, Modified Bernoulli Vacation, Bernoulli Feedback, Breakdown, Delaying Repair And Reneging, G. Ayyappan, J. Udayageetha
Applications and Applied Mathematics: An International Journal (AAM)
This paper considers a queuing system which facilitates a single server that serves two classes of units: high priority and low priority units. These two classes of units arrive at the system in two independent compound Poisson processes. It aims to decipher average queue size and average waiting time of the units. Under the pre-emptive priority rule, the server provides a general service to these arriving units. It is further assumed the server may take a vacation after serving the last high priority unit present in the system or at the service completion of each low priority unit present in …
Analysis Of A M/M/C Queue With Single And Multiple Synchronous Working Vacations, Shakir Majid, P. Manoharan
Analysis Of A M/M/C Queue With Single And Multiple Synchronous Working Vacations, Shakir Majid, P. Manoharan
Applications and Applied Mathematics: An International Journal (AAM)
We consider a M/M/c queuing system with synchronous working vacation and two different policies of working vacation i.e. a multiple working vacation policy and a single working policy. During a working vacation the server does not completely halts the service rather than it will render service at a lower rate. In synchronous vacation policy all the servers leave for a vacation simultaneously, when the server finds the system empty after finishing serving a customer. In multiple working vacation (MWV) policy the servers continue to take vacation till they find the system nonempty at a vacation completion instant. Single working vacation …
Exponentiated Weibull-Exponential Distribution With Applications, M. Elgarhy, M. Shakil, B. M. Golam Kibria
Exponentiated Weibull-Exponential Distribution With Applications, M. Elgarhy, M. Shakil, B. M. Golam Kibria
Applications and Applied Mathematics: An International Journal (AAM)
In this article, a new four-parameter continuous model, called the exponentiated Weibull exponential distribution, is introduced based on exponentiated Weibull-G family (Hassan and Elgarhy, 2016). The new model contains some new distributions as well as some former distributions. Various mathematical properties of this distribution are studied. General explicit expressions for the quantile function, expansion of distribution and density functions, moments, generating function, Rényi and q – entropies, and order statistics are obtained. The estimation of the model parameters is discussed using maximum likelihood method. The practical importance of the new distribution is demonstrated through real data set where we compare …