Inference For The Rayleigh Distribution Based On Progressive Type-Ii Fuzzy Censored Data,
2014
Shahid Chamran University, Ahvaz, Iran
Inference For The Rayleigh Distribution Based On Progressive Type-Ii Fuzzy Censored Data, Abbas Pak, Gholam Ali Parham, Mansour Saraj
Journal of Modern Applied Statistical Methods
Classical statistical analysis of the Rayleigh distribution deals with precise information. However, in real world situations, experimental performance results cannot always be recorded or measured precisely, but each observable event may only be identified with a fuzzy subset of the sample space. Therefore, the conventional procedures used for estimating the Rayleigh distribution parameter will need to be adapted to the new situation. This article discusses different estimation methods for the parameters of the Rayleigh distribution on the basis of a progressively type-II censoring scheme when the available observations are described by means of fuzzy information. They include the maximum likelihood …
Distance Correlation Coefficient: An Application With Bayesian Approach In Clinical Data Analysis,
2014
Malabar Cancer Centre, Kerala, India
Distance Correlation Coefficient: An Application With Bayesian Approach In Clinical Data Analysis, Atanu Bhattacharjee
Journal of Modern Applied Statistical Methods
The distance correlation coefficient – based on the product-moment approach – is one method by which to explore the relationship between variables. The Bayesian approach is a powerful tool to determine statistical inferences with credible intervals. Prior information about the relationship between BP and Serum cholesterol was applied to formulate the distance correlation between the two variables. The conjugate prior is considered to formulate the posterior estimates of the distance correlations. The illustrated method is simple and is suitable for other experimental studies.
Some New Probability Distributions Based On Random Extrema And Permutation Patterns,
2014
East Tennessee State University
Some New Probability Distributions Based On Random Extrema And Permutation Patterns, Jie Hao
Electronic Theses and Dissertations
In this paper, we study a new family of random variables, that arise as the distribution of extrema of a random number N of independent and identically distributed random variables X1,X2, ..., XN, where each Xi has a common continuous distribution with support on [0,1]. The general scheme is first outlined, and SUG and CSUG models are introduced in detail where Xi is distributed as U[0,1]. Some features of the proposed distributions can be studied via its mean, variance, moments and moment-generating function. Moreover, we make some other choices for …
Median Based Modified Ratio Estimators With Known Quartiles Of An Auxiliary Variable,
2014
Pondicherry University, Puducherry, India
Median Based Modified Ratio Estimators With Known Quartiles Of An Auxiliary Variable, Jambulingam Subramani, G Prabavathy
Journal of Modern Applied Statistical Methods
New median based modified ratio estimators for estimating a finite population mean using quartiles and functions of an auxiliary variable are proposed. The bias and mean squared error of the proposed estimators are obtained and the mean squared error of the proposed estimators are compared with the usual simple random sampling without replacement (SRSWOR) sample mean, ratio estimator, a few existing modified ratio estimators, the linear regression estimator and median based ratio estimator for certain natural populations. A numerical study shows that the proposed estimators perform better than existing estimators; in addition, it is shown that the proposed median based …
On The Exponentiated Weibull Distribution For Modeling Wind Speed In South Western Nigeria,
2014
University of Ibadan, Nigeria
On The Exponentiated Weibull Distribution For Modeling Wind Speed In South Western Nigeria, Olanrewaju I. Shittu, K A. Adepoju
Journal of Modern Applied Statistical Methods
One of the bases for assessment of wind energy potential for a specified region is the probability distribution of wind speed. Thus, appropriate and adequate specification of the probability distribution of wind speed becomes increasingly important. Several distributions have been proposed for describing wind distribution. Among the most popular distributions is the Weibull whose choice is due to its flexibility. An exponentiated Weibull distribution is proposed as an alternative to model wind speed data with a view to comparing it with the existing Weibull distribution. Results indicate that the proposed distribution outperforms the existing Weibull distribution for modeling wind speed …
Robust Regression Analysis For Non-Normal Situations Under Symmetric Distributions Arising In Medical Research,
2014
Sultan Qaboos University, Muscat, Oman
Robust Regression Analysis For Non-Normal Situations Under Symmetric Distributions Arising In Medical Research, S S. Ganguly
Journal of Modern Applied Statistical Methods
In medical research, while carrying out regression analysis, it is usually assumed that the independent (covariates) and dependent (response) variables follow a multivariate normal distribution. In some situations, the covariates may not have normal distribution and instead may have some symmetric distribution. In such a situation, the estimation of the regression parameters using Tiku’s Modified Maximum Likelihood (MML) method may be more appropriate. The method of estimating the parameters is discussed and the applications of the method are illustrated using real sets of data from the field of public health.
Jmasm 33: A Two Dependent Samples Maximum Test Calculator: Excel,
2014
Wayne State University
Jmasm 33: A Two Dependent Samples Maximum Test Calculator: Excel, Saverpierre Maggio, Shlomo Sawilowsky
Journal of Modern Applied Statistical Methods
An Excel Macro was created to provide researchers with an easy to use resource in order to calculate the two dependent samples maximum test as provided in Maggio and Sawilowsky (2014), which permits conducting both the two dependent samples t-test and Wilcoxon signed-ranks test on the same data while eliminating concerns related to Type I error inflation and choice of statistical tests.
Vol. 13, No. 1 (Full Issue),
2014
Wayne State University
Vol. 13, No. 1 (Full Issue), Jmasm Editors
Journal of Modern Applied Statistical Methods
No abstract provided.
Relative Importance Of Predictors In Multilevel Modeling,
2014
Harvard University
Relative Importance Of Predictors In Multilevel Modeling, Yan Liu, Bruno D. Zumbo, Amery D. Wu
Journal of Modern Applied Statistical Methods
The Pratt index is a useful and practical strategy for day-to-day researchers when ordering predictors in a multiple regression analysis. The purposes of this study are to introduce and demonstrate the use of the Pratt index to assess the relative importance of predictors for a random intercept multilevel model.
Predicting Survival Time Of Localized Melanoma Patients Using Discrete Survival Time Method,
2014
University of South Florida
Predicting Survival Time Of Localized Melanoma Patients Using Discrete Survival Time Method, Taysseer Sharaf, Chris P. Tsokos
Journal of Modern Applied Statistical Methods
Melanoma is the most fatal type of skin cancer. It is ranked first in death of skin cancer diseases. This study establishes a statistical model that can predict the survival time of localized melanoma patients, as a function of age at diagnosis, tumor thickness, and extension of the tumor (tumor invasion). The discrete time survival method was used to build the statistical model. The patients involved in the current study were observed from the SEER database. Patients were divided into nine groups according to age at diagnosis. Variation in survival time was found to be significant among some of the …
Population Mean Estimation With Sub Sampling The Non-Respondents Using Two Phase Sampling,
2014
Alliance University, Karnataka, India
Population Mean Estimation With Sub Sampling The Non-Respondents Using Two Phase Sampling, Sunil Kumar, M Viswanathaiah
Journal of Modern Applied Statistical Methods
The problem of non-response in double (or two phase) sampling is dealt with combined ratio, product and regression estimators. Expressions of bias and MSE for these estimators are obtained. Comparisons of a proposed strategy with a usual unbiased estimator and other estimators are carried out and results obtained are illustrated numerically using an empirical sample.
Estimation And Testing In Type-Ii Generalized Half Logistic Distribution,
2014
Acharya Nagarjuna University, India
Estimation And Testing In Type-Ii Generalized Half Logistic Distribution, R R. L. Kantam, V Ramakrishna, M S. Ravikumar
Journal of Modern Applied Statistical Methods
A generalization of the Half Logistic Distribution is developed through exponentiation of its survival function and named the Type II Generalized Half Logistic Distribution (GHLD). The distributional characteristics are presented and estimation of its parameters using maximum likelihood and modified maximum likelihood methods is studied with comparisons. Discrimination between Type II GHLD and exponential distribution in pairs is conducted via likelihood ratio criterion.
A Compound Of Geeta Distribution With Generalized Beta Distribution,
2014
University of Kashmir, Srinagar, India
A Compound Of Geeta Distribution With Generalized Beta Distribution, Adil Rashid, T R. Jan
Journal of Modern Applied Statistical Methods
A compound of Geeta distribution with Generalized Beta distribution (GBD) is obtained and the compound is specialized for different values of β. The first order factorial moments of some special compound distributions are also obtained. A chronological overview of recent developments in the compounding of distributions is provided in the introduction.
Hierarchical Clustering With Simple Matching And Joint Entropy Dissimilarity Measure,
2014
Marmara University, Istanbul, Turkey
Hierarchical Clustering With Simple Matching And Joint Entropy Dissimilarity Measure, A Mete ÇilingtüRk, ÖZlem ErgüT
Journal of Modern Applied Statistical Methods
Conventional clustering algorithms are restricted for use with data containing ratio or interval scale variables; hence, distances are used. As social studies require merely categorical data, the literature is enriched with more complicated clustering techniques and algorithms of categorical data. These techniques are based on similarity or dissimilarity matrices. The algorithms are using density based or pattern based approaches. A probabilistic nature to similarity structure is proposed. The entropy dissimilarity measure has comparable results with simple matching dissimilarity at hierarchical clustering. It overcomes dimension increase through binarization of the categorical data. This approach is also functional with the clustering methods, …
An Exploratory Graphical Method For Identifying Associations In R X C Contingency Tables,
2014
Feinstein Institute for Medical Research
An Exploratory Graphical Method For Identifying Associations In R X C Contingency Tables, Martin L. Lesser, Meredith B. Akerman
Journal of Modern Applied Statistical Methods
On finding a significant association between rows and columns of an r x c contingency table, the next step is to study the nature of the association in more detail. The use of a scree plot to visualize the largest contributions to Χ2 among all cells in the table in order to determine the nature of the association in more detail is proposed.
Separate Ratio-Type Estimators Of Population Mean In Stratified Random Sampling,
2014
Vikram University, Ujjain, M.P., India
Separate Ratio-Type Estimators Of Population Mean In Stratified Random Sampling, Rajesh Tailor, Hilal A. Lone
Journal of Modern Applied Statistical Methods
Separate ratio-type estimators for population mean with their properties are considered. Some separate ratio-type estimators for population mean using known parameters of auxiliary variate are proposed. The bias and mean squared error of the proposed estimators are obtained up to the first degree of approximation. It is shown that the proposed estimators are more efficient than unbiased estimators in stratified random sampling and usual separate ratio estimators under certain obtained conditions. To judge the merits of the proposed estimators, an empirical study was conducted.
Evaluation Of Area Under The Constant Shape Bi-Weibull Roc Curve,
2014
Pondicherry University, Puducherry, India
Evaluation Of Area Under The Constant Shape Bi-Weibull Roc Curve, Sudesh Pundir, R Amala
Journal of Modern Applied Statistical Methods
The Receiver Operating Characteristic (ROC) curve generated based on assuming a constant shape Bi-Weibull distribution is studied. In the context of ROC curve analysis, it is assumed that biomarker values from controls and cases follow some specific distribution and the accuracy is evaluated by using the ROC model developed from that specified distribution. This article assumes that the biomarker values from the two groups follow Weibull distributions with equal shape parameter and different scale parameters. The ROC model, area under the ROC curve (AUC), asymptotic and bootstrap confidence intervals for the AUC are derived. Theoretical results are validated by simulation …
Investigating The Feasibility Of Using Mplus In The Estimation Of Growth Mixture Models,
2014
University of Maryland
Investigating The Feasibility Of Using Mplus In The Estimation Of Growth Mixture Models, Ming Li, Jeffrey R. Harring, George B. Macready
Journal of Modern Applied Statistical Methods
Hipp and Bauer (2006) investigated the issues of singularities and local maximum solutions within growth mixture models (GMMs) and made recommendations regarding the use of multiple starting values. Building on their work, this simulation study investigates the feasibility of estimating GMMs within Mplus as measured by convergence to proper, but local solutions.
A Reduced Bias Method Of Estimating Variance Components In Generalized Linear Mixed Models,
2014
University of Nebraska-Lincoln
A Reduced Bias Method Of Estimating Variance Components In Generalized Linear Mixed Models, Elizabeth A. Claassen
Department of Statistics: Dissertations, Theses, and Student Research
In small samples it is well known that the standard methods for estimating variance components in a generalized linear mixed model (GLMM), pseudo-likelihood and maximum likelihood, yield estimates that are biased downward. An important consequence of this is that inferences on fixed effects will have inflated Type I error rates because their precision is overstated. We introduce a new method for estimating parameters in GLMMs that applies a Firth bias adjustment to the maximum likelihood-based GLMM estimating algorithm. We apply this technique to one- and two-treatment logistic regression models with a single random effect. We show simulation results that demonstrate …
Comparison Of Different Methods For Estimating Log-Normal Means,
2014
East Tennessee State University
Comparison Of Different Methods For Estimating Log-Normal Means, Qi Tang
Electronic Theses and Dissertations
The log-normal distribution is a popular model in many areas, especially in biostatistics and survival analysis where the data tend to be right skewed. In our research, a total of ten different estimators of log-normal means are compared theoretically. Simulations are done using different values of parameters and sample size. As a result of comparison, ``A degree of freedom adjusted" maximum likelihood estimator and Bayesian estimator under quadratic loss are the best when using the mean square error (MSE) as a criterion. The ten estimators are applied to a real dataset, an environmental study from Naval Construction Battalion Center (NCBC), …
