Approximating The Distribution Of Indefinite Quadratic Forms In Normal Variables By Maximum Entropy Density Estimation,
2017
Abadan Branch, Islamic Azad University, Abadan, Iran
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 …
Semi-Parametric Method To Estimate The Time-To-Failure Distribution And Its Percentiles For Simple Linear Degradation Model,
2017
Yarmouk University, Irbid, Jordan
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 …
Jmasm 48: The Pearson Product-Moment Correlation Coefficient And Adjustment Indices: The Fisher Approximate Unbiased Estimator And The Olkin-Pratt Adjustment (Spss),
2017
Northern Illinois University
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.
Inferential Procedures For Log Logistic Distribution With Doubly Interval Censored Data,
2017
Universiti Putra Malaysia, Seri Kembangan, Malaysia
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.
On Poisson Quasi-Lindley Distribution And Its Applications,
2017
Badji-Mokhtar University, Annaba, Algeria
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,
2017
University Putra Malaysia, Serdang, Malaysia
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.
Modeling Agreement Between Binary Classifications Of Multiple Raters In R And Sas,
2017
Boston University
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.
Jmasm 49: A Compilation Of Some Popular Goodness Of Fit Tests For Normal Distribution: Their Algorithms And Matlab Codes (Matlab),
2017
Manisa Celal Bayar University, Manisa, Turkey
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.
The Impact Of Predictor Variable(S) With Skewed Cell Probabilities On Wald Tests In Binary Logistic Regression,
2017
University of British Columbia
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 50: A Web-Based Shiny Application For Conducting A Two Dependent Samples Maximum Test (R),
2017
Wayne State University
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.
Jmasm 47: Anova_Hov: A Sas Macro For Testing Homogeneity Of Variance In One-Factor Anova Models (Sas),
2017
University of South Florida, Tampa, FL
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.
A Remark For The Admissibility Of Rao’S U-Test,
2017
Northeast Normal University, Changchun, Jilin, China
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,
2017
Wayne State University
Vol. 16, No. 2 (Full Issue),
2017
Wayne State University
Vol. 16, No. 2 (Full Issue), Jmasm Editors
Journal of Modern Applied Statistical Methods
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'Parallel Universe' Or 'Proven Future'? The Language Of Dependent Means T-Test Interpretations,
2017
Université Laval, Quebec City
'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 …
Unit Root Test For Panel Data Ar(1) Time Series Model With Linear Time Trend And Augmentation Term: A Bayesian Approach,
2017
Central University of Rajasthan, India
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 …
End Matter,
2017
Wayne State University
Characterizations Of Distributions By Expected Values Of Lower Record Statistics With Spacing,
2017
Aligarh Muslim University, Aligarh, India
Characterizations Of Distributions By Expected Values Of Lower Record Statistics With Spacing, M. Faizan, Ziaul Haque, M. A. Ansari
Journal of Modern Applied Statistical Methods
The characterizations of a certain class of probability distributions are established through conditional expectation of lower record values when the conditioned record value may not be the adjacent one. Some of its important deductions are also discussed.
Using Pratt's Importance Measures In Confirmatory Factor Analyses,
2017
University of British Columbia
Using Pratt's Importance Measures In Confirmatory Factor Analyses, Amrey D. Wu, Bruno D. Zumbo
Journal of Modern Applied Statistical Methods
When running a confirmatory factor analysis (CFA), users specify and interpret the pattern (loading) matrix. It has been recommended that the structure coefficients, indicating the factors’ correlation with the observed indicators, should also be reported when the factors are correlated (Graham, Guthrie, & Thompson, 2003; Thompson, 1997). The aims of this article are: (1) to note the structure coefficient should be interpreted with caution if the factors are specified to correlate. Because the structure coefficient is a zero-order correlation, it may be partially or entirely a reflection of factor correlations. This is elucidated by the matrix algebra of the structure …
A Double Ewma Control Chart For The Individuals Based On A Linear Prediction,
2017
University of Northern California
A Double Ewma Control Chart For The Individuals Based On A Linear Prediction, Rafael Perez Abreu, Jay R. Schaffer
Journal of Modern Applied Statistical Methods
Industrial process use single and double Exponential Weighted Moving Average control charts to detect small shifts in it. Occasionally there is a need to detect small trends instead of shifts, but the effectiveness to detect small trends. A new control chart is proposed to detect a small drift.
