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Articles 31 - 60 of 77
Full-Text Articles in Physical Sciences and Mathematics
Front Matter, Jmasm Editors
End Matter, Jmasm Editors
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
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
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 …
Rao-Lovric And The Triwizard Point Null Hypothesis Tournament, Shlomo Sawilowsky
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.
Study Of The Left Censored Data From The Gumbel Type Ii Distribution Under A Bayesian Approach, Tabassum Naz Sindhu, Navid Feroze, Muhammad Aslam
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.
Vol. 15, No. 2 (Full Issue), Jmasm Editors
Vol. 15, No. 2 (Full Issue), Jmasm Editors
Journal of Modern Applied Statistical Methods
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Misspecification Of Variants Of Autoregressive Garch Models And Effect On In-Sample Forecasting, Olusanya E. Olubusoye, Olaoluwa S. Yaya, Oluwadare O. Ojo
Misspecification Of Variants Of Autoregressive Garch Models And Effect On In-Sample Forecasting, Olusanya E. Olubusoye, Olaoluwa S. Yaya, Oluwadare O. Ojo
Journal of Modern Applied Statistical Methods
Generally, in empirical financial studies, the determination of the true conditional variance in GARCH modelling is largely subjective. In this paper, we investigate the consequences of choosing a wrong conditional variance specification. The methodology involves specifying a true conditional variance and then simulating data to conform to the true specification. The estimation is then carried out using the true specification and other plausible specification that are appealing to the researcher, using model and forecast evaluation criteria for assessing performance. The results show that GARCH model could serve as better alternative to other asymmetric volatility models.
Estimation Of Parameters Of Misclassified Size Biased Borel Distribution, Bhaktida S. Trivedi, M. N. Patel
Estimation Of Parameters Of Misclassified Size Biased Borel Distribution, Bhaktida S. Trivedi, M. N. Patel
Journal of Modern Applied Statistical Methods
A misclassified size-biased Borel Distribution (MSBBD), where some of the observations corresponding to x = c + 1 are wrongly reported as x = c with probability α, is defined. Various estimation methods like the method of maximum likelihood (ML), method of moments, and the Bayes estimation for the parameters of the MSBB distribution are used. The performance of the estimators are studied using simulated bias and simulated risk. Simulation studies are carried out for different values of the parameters and sample size.
Some Tests For Seasonality In Time Series Data, Eleazar Chukwunenye Nwogu, Iheanyi Sylvester Iwueze, Valentine Uchenna Nlebedim
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
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
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
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.
A Comprehensive Review Of The Two-Sample Independent Or Paired Binary Data, With Or Without Stratum Effects, Dewi Rahardja, Ying Yang, Zhiwei Zhang
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 …
Improved Ridge Estimator In Linear Regression With Multicollinearity, Heteroscedastic Errors And Outliers, Ashok Vithoba Dorugade
Improved Ridge Estimator In Linear Regression With Multicollinearity, Heteroscedastic Errors And Outliers, Ashok Vithoba Dorugade
Journal of Modern Applied Statistical Methods
This paper introduces a new estimator, of ridge parameter k for ridge regression and then evaluated by Monte Carlo simulation. We examine the performance of the proposed estimators compared with other well-known estimators for the model with heteroscedastics and/or correlated errors, outlier observations, non-normal errors and suffer from the problem of multicollinearity. It is shown that proposed estimators have a smaller MSE than the ordinary least squared estimator (LS), Hoerl and Kennard (1970) estimator (RR), jackknifed modified ridge (JMR) estimator, and Jackknifed Ridge M‑estimator (JRM).
Bayesian Analysis Of Generalized Exponential Distribution, Saima Naqash, S. P. Ahmad, Aquil Ahmed
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.
Jmasm41: An Alternative Method For Multiple Linear Model Regression Modeling, A Technical Combining Of Robust, Bootstrap And Fuzzy Approach (Sas), Wan Muhamad Amir W Ahmad, Mohamad Arif Awang Nawi, Nor Azlida Aleng, Mohamad Shafiq
Jmasm41: An Alternative Method For Multiple Linear Model Regression Modeling, A Technical Combining Of Robust, Bootstrap And Fuzzy Approach (Sas), Wan Muhamad Amir W Ahmad, Mohamad Arif Awang Nawi, Nor Azlida Aleng, Mohamad Shafiq
Journal of Modern Applied Statistical Methods
Research on modeling is becoming popular nowadays, there are several of analyses used in research for modeling and one of them is known as applied multiple linear regressions (MLR). To obtain a bootstrap, robust and fuzzy multiple linear regressions, an experienced researchers should be aware the correct method of statistical analysis in order to get a better improved result. The main idea of bootstrapping is to approximate the entire sampling distribution of some estimator. To achieve this is by resampling from our original sample. In this paper, we emphasized on combining and modeling using bootstrapping, robust and fuzzy regression methodology. …
Jmasm42: An Alternative Algorithm And Programming Implementation For Least Absolute Deviation Estimator Of The Linear Regression Models (R), Suraju Olaniyi Ogundele, J. I. Mbegbu, C. R. Nwosu
Jmasm42: An Alternative Algorithm And Programming Implementation For Least Absolute Deviation Estimator Of The Linear Regression Models (R), Suraju Olaniyi Ogundele, J. I. Mbegbu, C. R. Nwosu
Journal of Modern Applied Statistical Methods
We propose a least absolute deviation estimation method that produced a least absolute deviation estimator of parameter of the linear regression model. The method is as accurate as existing method.
A Generalization Of The Weibull Distribution With Applications, Maalee Almheidat, Carl Lee, Felix Famoye
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 …
Graphing Effects As Fuzzy Numbers In Meta-Analysis, Christopher G. Thompson
Graphing Effects As Fuzzy Numbers In Meta-Analysis, Christopher G. Thompson
Journal of Modern Applied Statistical Methods
Prior to quantitative analyses, meta-analysts often explore descriptive characteristics of effect sizes. A graphic is proposed that treats effect sizes as fuzzy numbers. This plot can provide meta-analysts with such information such as heterogeneity of effects, precision of estimates, possible clusters, and existence of outliers.
Principal Component Preliminary Test Estimator In The Linear Regression Model, Sivarajah Arumairajan, Pushpakanthie Wijekoon
Principal Component Preliminary Test Estimator In The Linear Regression Model, Sivarajah Arumairajan, Pushpakanthie Wijekoon
Journal of Modern Applied Statistical Methods
A Preliminary Test Estimator is introduced based on Principal Component Regression Estimator defined in the linear regression model when the stochastic restrictions are available in addition to the sample information, and when the explanatory variables are multicollinear. It is further developed as a large sample preliminary test estimator by using Wald (WA), Likelihood Ratio (LR), and Lagrangian Multiplier (LM) tests. Stochastic properties of this estimator based on F test as well as WA, LR, and LM tests are derived, and the performance of the estimator is compared using WA, LR, and LM tests with respect to Mean Square Error Matrix …
Analysis And Modeling Of Statistical Properties Of Fmdfb Subband Coefficients, E. Jebamalar Leavline, Sutha Shunmugam
Analysis And Modeling Of Statistical Properties Of Fmdfb Subband Coefficients, E. Jebamalar Leavline, Sutha Shunmugam
Journal of Modern Applied Statistical Methods
Fast Multiscale Directional Filter Bank (FMDFB) is an image representation scheme used in several image processing applications. The statistical nature of the FMDFB subbands is analyzed, and a mathematical model of FMDFB coefficients is proposed. Experimental results are justified by goodness-of-fit tests.
Jmasm37: Simple Response Surface Methodology Using Rsreg (Sas), Wan Muhamad Amir, Mohamad Shafiq, Kasypi Mokhtar, Nor Azlida Aleng, Hanafi A.Rahim, Zalila Ali
Jmasm37: Simple Response Surface Methodology Using Rsreg (Sas), Wan Muhamad Amir, Mohamad Shafiq, Kasypi Mokhtar, Nor Azlida Aleng, Hanafi A.Rahim, Zalila Ali
Journal of Modern Applied Statistical Methods
Response surface methodology (RSM) can be used when the response variable, y, is influenced by several variables, x’s. When treatments take the form of quantitative values, then the true relationship between response variables and independent variables might be known. Examples are given in SAS.
Generalized Singular Value Decomposition With Additive Components, Stan Lipovetsky
Generalized Singular Value Decomposition With Additive Components, Stan Lipovetsky
Journal of Modern Applied Statistical Methods
The singular value decomposition (SVD) technique is extended to incorporate the additive components for approximation of a rectangular matrix by the outer products of vectors. While dual vectors of the regular SVD can be expressed one via linear transformation of the other, the modified SVD corresponds to the general linear transformation with the additive part. The method obtained can be related to the family of principal component and correspondence analyses, and can be reduced to an eigenproblem of a specific transformation of a data matrix. This technique is applied to constructing dual eigenvectors for data visualizing in a two dimensional …
New Procedures Of Estimating Proportion And Sensitivity Using Randomized Response In A Dichotomous Finite Population, Tanveer A. Tarray, Housila P. Singh
New Procedures Of Estimating Proportion And Sensitivity Using Randomized Response In A Dichotomous Finite Population, Tanveer A. Tarray, Housila P. Singh
Journal of Modern Applied Statistical Methods
The problem of estimating the population proportion possessing a sensitive attribute using simple random sampling with replacement (SRSWR) is advocated. Two new procedures are proposed. The suggested models are more efficient than the Huang (2004) randomized response technique under some realistic conditions. Numerical and graphic illustrations are given.
Application Of Esscher Transformed Laplace Distribution In Microarray Gene Expression Data, Shanmugasundaram Devika, Sebastian George, Lakshmanan Jeyaseelan
Application Of Esscher Transformed Laplace Distribution In Microarray Gene Expression Data, Shanmugasundaram Devika, Sebastian George, Lakshmanan Jeyaseelan
Journal of Modern Applied Statistical Methods
Microarrays allow the study of the expression profile of hundreds to thousands of genes simultaneously. These expressions could be from treated samples and the healthy controls. The Esscher transformed Laplace distribution is used to fit microarray expression data as compared to Normal and Laplace distributions. The Maximum Likelihood Estimation procedure is used to estimate the parameters of the distribution. R codes are developed to implement the estimation procedure. A simulation study is carried out to test the performance of the algorithm. AIC and BIC criterion are used to compare the distributions. It is shown that the fit of the Esscher …
Variable Selection In Regression Using Multilayer Feedforward Network, Tejaswi S. Kamble, Dattatraya N. Kashid
Variable Selection In Regression Using Multilayer Feedforward Network, Tejaswi S. Kamble, Dattatraya N. Kashid
Journal of Modern Applied Statistical Methods
The selection of relevant variables in the model is one of the important problems in regression analysis. Recently, a few methods were developed based on a model free approach. A multilayer feedforward neural network model was proposed for developing variable selection in regression. A simulation study and real data were used for evaluating the performance of proposed method in the presence of outliers, and multicollinearity.
The Goldilocks Dilemma: Impacts Of Multicollinearity -- A Comparison Of Simple Linear Regression, Multiple Regression, And Ordered Variable Regression Models, Grayson L. Baird, Stephen L. Bieber
The Goldilocks Dilemma: Impacts Of Multicollinearity -- A Comparison Of Simple Linear Regression, Multiple Regression, And Ordered Variable Regression Models, Grayson L. Baird, Stephen L. Bieber
Journal of Modern Applied Statistical Methods
A common consideration concerning the application of multiple linear regression is the lack of independence among predictors (multicollinearity). The main purpose of this article is to introduce an alternative method of regression originally outlined by Woolf (1951), which completely eliminates the relatedness between the predictors in a multiple predictor setting.
Symmetric Variants Of Logistic Smooth Transition Autoregressive Models: Monte Carlo Evidences, Olaoluwa S. Yaya, Olanrewaju I. Shittu
Symmetric Variants Of Logistic Smooth Transition Autoregressive Models: Monte Carlo Evidences, Olaoluwa S. Yaya, Olanrewaju I. Shittu
Journal of Modern Applied Statistical Methods
The Smooth Transition Autoregressive (STAR) models are becoming popular in modeling economic and financial time series. The asymmetric type of the model is the Logistic STAR (LSTAR) model, which is limited in its applications as a result of its asymmetric property, which makes it suitable for modelling specific macroeconomic time series. This study was designed to develop the Absolute Error LSTAR (AELSTAR) and Quadratic LSTAR (QLSTAR) models for improving symmetry and performance in terms of model fitness. Modified Teräsvirta’s Procedure (TP) and Escribano and Jordá's Procedure (EJP) were used to test for nonlinearity in the series. The performance of the …
Liu-Type Logistic Estimators With Optimal Shrinkage Parameter, Yasin Asar
Liu-Type Logistic Estimators With Optimal Shrinkage Parameter, Yasin Asar
Journal of Modern Applied Statistical Methods
Multicollinearity in logistic regression affects the variance of the maximum likelihood estimator negatively. In this study, Liu-type estimators are used to reduce the variance and overcome the multicollinearity by applying some existing ridge regression estimators to the case of logistic regression model. A Monte Carlo simulation is given to evaluate the performances of these estimators when the optimal shrinkage parameter is used in the Liu-type estimators, along with an application of real case data.