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Articles 1 - 30 of 75
Full-Text Articles in Physical Sciences and Mathematics
The Mx/G/1 Queue With Unreliable Server, Delayed Repairs, And Bernoulli Vacation Schedule Under T-Policy, L. Tadj, G. Choudhury
The Mx/G/1 Queue With Unreliable Server, Delayed Repairs, And Bernoulli Vacation Schedule Under T-Policy, L. Tadj, G. Choudhury
Applications and Applied Mathematics: An International Journal (AAM)
In this paper we study a batch arrival queuing system. The server may break down while delivering service. However, repair is not provided immediately, rather it is delayed for a random amount of time. At the end of service, the server may process the next customer if any are available, or may take a vacation to execute some other job. Finally, the server implements the T-policy. We describe for this system an optimal management policy. Numerical examples are provided.
Local Influence In Bayesian Elliptically Contoured-Ordinal Model For Mixed Data, Ehsan B. Samani
Local Influence In Bayesian Elliptically Contoured-Ordinal Model For Mixed Data, Ehsan B. Samani
Applications and Applied Mathematics: An International Journal (AAM)
This paper develops a new class of joint modeling of mixed correlated ordinal and continuous responses with elliptically contoured errors. This joint model includes the latent variable approach of using an elliptically contoured distribution for mixed ordinal and continuous responses. A Markov Chain Monte Carlo sampling algorithm is described for estimating the posterior distribution of the parameters. For sensitivity analysis to investigate the perturbation from associate responses, it is demonstrated how one can use some elements of covariance structure. Influence of small perturbation of these elements on the posterior normal curvature is also studied. To illustrate the application of such …
Using Fuzzy Linear Regression To Estimate Relationship Between Forest Fires And Meteorological Conditions, Hande G. Akdemir, Fatma Tiryaki
Using Fuzzy Linear Regression To Estimate Relationship Between Forest Fires And Meteorological Conditions, Hande G. Akdemir, Fatma Tiryaki
Applications and Applied Mathematics: An International Journal (AAM)
Each year, millions of hectares of forest land are destroyed by fires causing great financial loss and ecological damage. In this paper, our aim is to study the effect of the variation of meteorological conditions on the total burned area in hectares, by using fuzzy linear regression analysis based on Tanaka’s approaches. The total burned area is considered a dependent variable. Air temperature (in ºC), relative humidity (in %), wind speed (in km/h) and rainfall (in mm/m2 ) are considered to be independent variables. The relationship between input and output data is estimated using data provided in data mining …
Certain Fractional Integral Operators And The Generalized Incomplete Hypergeometric Functions, H. M. Srivastava, Praveen Agarwal
Certain Fractional Integral Operators And The Generalized Incomplete Hypergeometric Functions, H. M. Srivastava, Praveen Agarwal
Applications and Applied Mathematics: An International Journal (AAM)
In this paper, we apply a certain general pair of operators of fractional integration involving Appell’s function F3 in their kernel to the generalized incomplete hypergeometric functions pΓq[z] and pɣq [z], which were introduced and studied systematically by Srivastava et al. in the year 2012. Some interesting special cases and consequences of our main results are also considered.
Application Of Fractional Moments For Comparing Random Variables With Varying Probability Distributions, Munther R. Al Shami, A. R. Mugdadi, R. R. Nigmatullin, S. I. Osokin
Application Of Fractional Moments For Comparing Random Variables With Varying Probability Distributions, Munther R. Al Shami, A. R. Mugdadi, R. R. Nigmatullin, S. I. Osokin
Applications and Applied Mathematics: An International Journal (AAM)
New methods are being presented for statistical treatment of different random variables with unknown probability distributions. These include analysis based on the probability circles, probability ellipses, generalized mean values, generalized Pearson correlation coefficient and the beta-function analysis. Unlike other conventional statistical procedures, the main distinctive feature of these new methods is that no assumptions are made about the nature of the probability distribution of the random series being evaluated. Furthermore, the suggested procedures do not introduce uncontrollable errors during their application. The effectiveness of these methods is demonstrated on simulated data with extended and reduced sample sizes having different probability …
Analysis Of Mixed Correlated Bivariate Negative Binomial And Continuous Responses, F. Razie, E. B. Samani, M. Ganjali
Analysis Of Mixed Correlated Bivariate Negative Binomial And Continuous Responses, F. Razie, E. B. Samani, M. Ganjali
Applications and Applied Mathematics: An International Journal (AAM)
A general model for the mixed correlated negative binomial and continuous responses is proposed. It is shown how to construct parameter of the models, using the maximization of the full likelihood. Influence of a small perturbation of correlation parameter of the model on the likelihood displacement is also studied. The model is applied to a medical data, obtained from an observational study on women, where the correlated responses are the negative binomial response of joint damage and continuous responses of body mass index. Simultaneous effects of some covariates on both responses are investigated.
Preliminary Testing For Normality: Is This A Good Practice?, H. J. Keselman, Abdul R. Othman, Rand R. Wilcox
Preliminary Testing For Normality: Is This A Good Practice?, H. J. Keselman, Abdul R. Othman, Rand R. Wilcox
Journal of Modern Applied Statistical Methods
Normality is a distributional requirement of classical test statistics. In order for the test statistic to provide valid results leading to sound and reliable conclusions this requirement must be satisfied. In the not too distant past, it was claimed that violations of normality would not likely jeopardize scientific findings (See Hsu & Feldt, 1969; Lunney, 1970). Recent revelations suggest otherwise (See e.g., Micceri, 1989; Keselman, Huberty, Lix et al., 1998; Erceg-Hurn, Wilcox, & Keselman, 2013; Wilcox and Keselman, 2003; Wilcox, 2012a, b). Unfortunately the data obtained in psychological investigations rarely, if ever, meet the requirement of normally distributed data (Micceri, …
Front Matter, Jmasm Editors
Front Matter, Jmasm Editors
Journal of Modern Applied Statistical Methods
No abstract provided.
The Impact Of Continuity Violation On Anova And Alternative Methods, Björn Lantz
The Impact Of Continuity Violation On Anova And Alternative Methods, Björn Lantz
Journal of Modern Applied Statistical Methods
The normality assumption behind ANOVA and other parametric methods implies that response variables are measured on continuous scales. A simulation approach is used to explore the impact of continuity violation on the performance of statistical methods commonly used by applied researchers to compare locations across several groups.
Variables Sampling Plan For Correlated Data, J. R. Singh, R. Sankle, M. Ahmad Khanday
Variables Sampling Plan For Correlated Data, J. R. Singh, R. Sankle, M. Ahmad Khanday
Journal of Modern Applied Statistical Methods
The sampling plan for the mean for correlated data is studied. The Operating Characteristic (OC) of the variable sampling plan for mean for correlated data are calculated and compared with the OC of known σ case.
Intrinsically Ties Adjusted Non-Parametric Method For The Analysis Of Two Sampled Data, G. U. Ebuh, I. C. A Oyeka
Intrinsically Ties Adjusted Non-Parametric Method For The Analysis Of Two Sampled Data, G. U. Ebuh, I. C. A Oyeka
Journal of Modern Applied Statistical Methods
A non-parametric method for the analysis of two sample data is proposed that intrinsically and structurally adjusts the test statistic for the possible presence of tied observations between the sampled populations, thereby obviating the need to require the populations to be continuous. The populations may be measurements on as low as the ordinal scale, and need not be homogeneous. In cases where the null hypotheses are rejected, the test statistic enables the determination of which of the sampled populations is likely to be responsible for the rejection (a determination which the Wilcoxon Mann Whitney test cannot handle). The proposed method …
Case-Control Studies With Jointly Misclassified Exposure And Confounding Variables, Tze-San Lee
Case-Control Studies With Jointly Misclassified Exposure And Confounding Variables, Tze-San Lee
Journal of Modern Applied Statistical Methods
The issue of 2 × 2 × 2 case-control studies is addressed when both exposure and confounding variables are jointly misclassified. Two scenarios are considered: the classification errors of exposure and confounding variables are independent or not independent. The bias-adjusted cell probability estimates which account for the misclassification bias are presented. The effect of misclassification on the measure of crude odds ratio either unstratified or stratified by the confounder, Mantel-Haenszel summary odds ratio, the confounding component in the crude odds ratio, the first and second order multiplicative interaction are assessed through the sensitivity analysis from using the data on the …
How Good Is Best? Multivariate Case Of Ehrenberg-Weisberg Analysis Of Residual Errors In Competing Regressions, Stan Lipovetsky
How Good Is Best? Multivariate Case Of Ehrenberg-Weisberg Analysis Of Residual Errors In Competing Regressions, Stan Lipovetsky
Journal of Modern Applied Statistical Methods
A.S.C. Ehrenberg first noticed and S. Weisberg then formalized a property of pairwise regression to keep its quality almost at the same level of precision while the coefficients of the model could vary over a wide span of values. This paper generalizes the estimates of the percent change in the residual standard deviation to the case of competing multiple regressions. It shows that in contrast to the simple pairwise model, the coefficients of multiple regression can be changed over a wider range of the values including the opposite by signs coefficients. Consideration of these features facilitates better understanding the properties …
Constructing Confidence Intervals For Effect Sizes In Anova Designs, Li-Ting Chen, Chao-Ying Joanne Peng
Constructing Confidence Intervals For Effect Sizes In Anova Designs, Li-Ting Chen, Chao-Ying Joanne Peng
Journal of Modern Applied Statistical Methods
A confidence interval for effect sizes provides a range of plausible population effect sizes (ES) that are consistent with data. This article defines an ES as a standardized linear contrast of means. The noncentral method, Bonett’s method, and the bias-corrected and accelerated bootstrap method are illustrated for constructing the confidence interval for such an effect size. Results obtained from the three methods are discussed and interpretations of results are offered.
A Monte Carlo Comparison Of Robust Manova Test Statistics, Holmes Finch, Brian French
A Monte Carlo Comparison Of Robust Manova Test Statistics, Holmes Finch, Brian French
Journal of Modern Applied Statistical Methods
Multivariate Analysis of Variance (MANOVA) is a popular statistical tool in the social sciences, allowing for the comparison of mean vectors across groups. MANOVA rests on three primary assumptions regarding the population: (a) multivariate normality, (b) equality of group population covariance matrices and (c) independence of errors. When these assumptions are violated, MANOVA does not perform well with respect to Type I error and power. There are several alternative test statistics that can be considered including robust statistics and the use of the structural equation modeling (SEM) framework. This simulation study focused on comparing the performance of the P test …
Test For Intraclass Correlation Coefficient Under Unequal Family Sizes, Madhusudan Bhandary, Koji Fujiwara
Test For Intraclass Correlation Coefficient Under Unequal Family Sizes, Madhusudan Bhandary, Koji Fujiwara
Journal of Modern Applied Statistical Methods
Three tests are proposed based on F-distribution, Likelihood Ratio Test (LRT) and large sample Z-test for intraclass correlation coefficient under unequal family sizes based on a single multinormal sample. It has been found that the test based on F-distribution consistently and reliably produces results superior to those of Likelihood Ratio Test (LRT) and large sample Z-test in terms of size for various combinations of intraclass correlation coefficient values. The power of this test based on F-distribution is competitive with the power of the LRT and the power of Z-test is slightly better than the powers of F-test and LRT when …
Generalized Modified Ratio Estimator For Estimation Of Finite Population Mean, Jambulingam Subramani
Generalized Modified Ratio Estimator For Estimation Of Finite Population Mean, Jambulingam Subramani
Journal of Modern Applied Statistical Methods
A generalized modified ratio estimator is proposed for estimating the population mean using the known population parameters. It is shown that the simple random sampling without replacement sample mean, the usual ratio estimator, the linear regression estimator and all the existing modified ratio estimators are the particular cases of the proposed estimator. The bias and the mean squared error of the proposed estimator are derived and are compared with that of existing estimators. The conditions for which the proposed estimator performs better than the existing estimators are also derived. The performance of the proposed estimator is assessed with that of …
Discriminating Between Generalized Exponential Distribution And Some Life Test Models Based On Population Quantiles, B. Srinivasa Rao, R. R. L Kantam
Discriminating Between Generalized Exponential Distribution And Some Life Test Models Based On Population Quantiles, B. Srinivasa Rao, R. R. L Kantam
Journal of Modern Applied Statistical Methods
A test statistic based on population quantiles using sample order statistics is suggested. The quantiles of the test statistics are evaluated for generalized exponential distribution. Similar test statistic based on moments of sample order statistic is referred and the proposed test formula is compared with it. Between the pairs of the above models it is established that the test formula proposed by us is more effective and useful than the formula based on the moments of order statistics as developed by Sultan (2007).
Comparison Of Parameters Of Lognormal Distribution Based On The Classical And Posterior Estimates, Raja Sultan, S. P. Ahmad
Comparison Of Parameters Of Lognormal Distribution Based On The Classical And Posterior Estimates, Raja Sultan, S. P. Ahmad
Journal of Modern Applied Statistical Methods
Lognormal distribution is widely used in scientific field, such as agricultural, entomological, biology etc. If a variable can be thought as the multiplicative product of some positive independent random variables, then it could be modelled as lognormal. In this study, maximum likelihood estimates and posterior estimates of the parameters of lognormal distribution are obtained and using these estimates we calculate the point estimates of mean and variance for making comparisons.
On Bayesian Estimation And Predictions For Two-Component Mixture Of The Gompertz Distribution, Navid Feroze, Muhammad Aslam
On Bayesian Estimation And Predictions For Two-Component Mixture Of The Gompertz Distribution, Navid Feroze, Muhammad Aslam
Journal of Modern Applied Statistical Methods
Mixtures models have received sizeable attention from analysts in the recent years. Some work on Bayesian estimation of the parameters of mixture models have appeared. However, the were restricted to the Bayes point estimation The methodology for the Bayesian interval estimation of the parameters for said models is still to be explored. This paper proposes the posterior interval estimation (along with point estimation) for the parameters of a two-component mixture of the Gompertz distribution. The posterior predictive intervals are also derived and evaluated. Different informative and non-informative priors are assumed under a couple of loss functions for the posterior analysis. …
A Comparison Between Biased And Unbiased Estimators In Ordinary Least Squares Regression, Ghadban Khalaf
A Comparison Between Biased And Unbiased Estimators In Ordinary Least Squares Regression, Ghadban Khalaf
Journal of Modern Applied Statistical Methods
During the past years, different kinds of estimators have been proposed as alternatives to the Ordinary Least Squares (OLS) estimator for the estimation of the regression coefficients in the presence of multicollinearity. In the general linear regression model, Y = Xβ + e, it is known that multicollinearity makes statistical inference difficult and may even seriously distort the inference. Ridge regression, as viewed here, defines a class of estimators of β indexed by a scalar parameter k. Two methods of specifying k are proposed and evaluated in terms of Mean Square Error (MSE) by …
Parameter Estimations Based On Kumaraswamy Progressive Type Ii Censored Data With Random Removals, Navid Feroze, Ibrahim El-Batal
Parameter Estimations Based On Kumaraswamy Progressive Type Ii Censored Data With Random Removals, Navid Feroze, Ibrahim El-Batal
Journal of Modern Applied Statistical Methods
The estimation of two parameters of the Kumaraswamy distribution is considered under Type II progressive censoring with random removals, where the number of units removed at each failure time has a binomial distribution. The MLE was used to obtain the estimators of the unknown parameters, and the asymptotic variance - covariance matrix was also obtained. The formula to compute the expected test time was derived. A numerical study was carried out for different combinations of model parameters. Different censoring schemes were used for the estimation, and performance of these schemes was compared.
The Single-Case Data Analysis Package: Analysing Single-Case Experiments With R Software, Isis Bulté, Patrick Onghena
The Single-Case Data Analysis Package: Analysing Single-Case Experiments With R Software, Isis Bulté, Patrick Onghena
Journal of Modern Applied Statistical Methods
The RcmdrPlugin.SCDA plug-in package is discussed. It integrates three R packages in the R commander interface: SCVA (for Single-Case Visual Analysis), SCRT (for Single-Case Randomization Tests), and SCMA (for Single-Case Meta-Analysis). This way the plug-in package covers three important steps in the analysis of single-case data.
Comparison Of Three Calculation Methods For A Bayesian Inference Of P(Π1 > Π2), Yohei Kawasaki, Asanao Shimokawa, Etsuo Miyaoka
Comparison Of Three Calculation Methods For A Bayesian Inference Of P(Π1 > Π2), Yohei Kawasaki, Asanao Shimokawa, Etsuo Miyaoka
Journal of Modern Applied Statistical Methods
In Bayesian inference, some researchers have examined the difference of binominal proportions using θ = P(π1 > π2 − Δ0|X1,X2), where Xi denote binomial random variable with parameter πi. An approximate method and the MCMC method are compared with an exact method for θ, and results of actual clinical trials using θ are presented.
Bayesian Joinpoint Regression Model For Childhood Brain Cancer Mortality, Ram C. Kafle, Netra Khanal, Chris P. Tsokos
Bayesian Joinpoint Regression Model For Childhood Brain Cancer Mortality, Ram C. Kafle, Netra Khanal, Chris P. Tsokos
Journal of Modern Applied Statistical Methods
The Bayesian approach of joinpoint regression is widely used to analyze trends in cancer mortality, incidence and survival data. The Bayesian joinpoint regression model was used to study the childhood brain cancer mortality rate and its average percentage change (APC) per year. Annual observed mortality counts of children ages 0-19 from 1969-2009 obtained from Surveillance Epidemiology and End Results (SEER) database of National Cancer Institute (NCI) were analyzed. It was assumed that death counts are probabilistically characterized by the Poisson distribution and they were modeled using log link function. Results were compared with the mortality trend obtained using joinpoint software …
On Some Properties Of A Heterogeneous Transfer Function Involving Symmetric Saturated Linear (Satlins) With Hyperbolic Tangent (Tanh) Transfer Functions, Christopher Godwin Udomboso
On Some Properties Of A Heterogeneous Transfer Function Involving Symmetric Saturated Linear (Satlins) With Hyperbolic Tangent (Tanh) Transfer Functions, Christopher Godwin Udomboso
Journal of Modern Applied Statistical Methods
For transfer functions to map the input layer of the statistical neural network model to the output layer perfectly, they must lie within bounds that characterize probability distributions. The heterogeneous transfer function, SATLINS_TANH, is established as a Probability Distribution Function (p.d.f), and its mean and variance are shown.
Distribution Of The Ratio Of Normal And Rice Random Variables, Nayereh B. Khoolenjani, Kavoos Khorshidian
Distribution Of The Ratio Of Normal And Rice Random Variables, Nayereh B. Khoolenjani, Kavoos Khorshidian
Journal of Modern Applied Statistical Methods
The ratio of independent random variables arises in many applied problems. The distribution of the ratio |X/Y| is studied when X and Y are independent Normal and Rice random variables, respectively. Ratios of such random variables have extensive applications in the analysis of noises in communication systems. The exact forms of probability density function (PDF), cumulative distribution function (CDF) and the existing moments are derived in terms of several special functions. As a special case, the PDF and CDF of the ratio of independent standard Normal and Rayleigh random variables have been obtained. Tabulations of associated percentage points …
Robust Regression Estimators When There Are Tied Values, Rand R. Wilcox, Florence Clark
Robust Regression Estimators When There Are Tied Values, Rand R. Wilcox, Florence Clark
Journal of Modern Applied Statistical Methods
It is well known that when using the ordinary least squares regression estimator, outliers among the dependent variable can result in relatively poor power. Many robust regression estimators have been derived that address this problem, but the bulk of the results assume that the dependent variable is continuous. It is demonstrated that when there are tied values, several robust regression estimators can perform poorly in terms of controlling the Type I error probability, even with a large sample size. The presence of tied values does not necessarily mean that they perform poorly, but there is the issue of whether there …
A Generalized Class Of Estimators For Finite Population Variance In Presence Of Measurement Errors, Prayas Sharma, Rajesh Singh
A Generalized Class Of Estimators For Finite Population Variance In Presence Of Measurement Errors, Prayas Sharma, Rajesh Singh
Journal of Modern Applied Statistical Methods
The problem of estimating the population variance is presented using auxiliary information in the presence of measurement errors. The estimators in this article use auxiliary information to improve efficiency and assume that measurement error is present both in study and auxiliary variable. A numerical study is carried out to compare the performance of the proposed estimator with other estimators and the variance per unit estimator in the presence of measurement errors.
Testing The Assumption Of Non-Differential Misclassification In Case-Control Studies, Tze-San Lee, Qin Hui
Testing The Assumption Of Non-Differential Misclassification In Case-Control Studies, Tze-San Lee, Qin Hui
Journal of Modern Applied Statistical Methods
One of the not yet solved issues regarding the misclassification in case-control studies is whether the misclassification rates are the same for both cases and controls. Currently, a common practice is to assume that the rates are the same, that is, the non-differential misclassification assumption. However, it has been suspected that this assumption may not be valid in practical applications. Unfortunately, no test is available so far to test the validity of the non-differential misclassification assumption. A method is presented to test the validity of non-differential misclassification assumption in case-control studies with 2 × 2 tables when validation data are …