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Articles 541 - 570 of 1633

Full-Text Articles in Statistical Theory

Inference For The Rayleigh Distribution Based On Progressive Type-Ii Fuzzy Censored Data, Abbas Pak, Gholam Ali Parham, Mansour Saraj May 2014

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 …

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Distance Correlation Coefficient: An Application With Bayesian Approach In Clinical Data Analysis, Atanu Bhattacharjee May 2014

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.

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Some New Probability Distributions Based On Random Extrema And Permutation Patterns, Jie Hao May 2014

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 …

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Median Based Modified Ratio Estimators With Known Quartiles Of An Auxiliary Variable, Jambulingam Subramani, G Prabavathy May 2014

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 …

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On The Exponentiated Weibull Distribution For Modeling Wind Speed In South Western Nigeria, Olanrewaju I. Shittu, K A. Adepoju May 2014

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 …

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Robust Regression Analysis For Non-Normal Situations Under Symmetric Distributions Arising In Medical Research, S S. Ganguly May 2014

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.

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Jmasm 33: A Two Dependent Samples Maximum Test Calculator: Excel, Saverpierre Maggio, Shlomo Sawilowsky May 2014

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.

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Vol. 13, No. 1 (Full Issue), Jmasm Editors May 2014

Vol. 13, No. 1 (Full Issue), Jmasm Editors

Journal of Modern Applied Statistical Methods

No abstract provided.

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Relative Importance Of Predictors In Multilevel Modeling, Yan Liu, Bruno D. Zumbo, Amery D. Wu May 2014

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.

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Predicting Survival Time Of Localized Melanoma Patients Using Discrete Survival Time Method, Taysseer Sharaf, Chris P. Tsokos May 2014

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 …

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Population Mean Estimation With Sub Sampling The Non-Respondents Using Two Phase Sampling, Sunil Kumar, M Viswanathaiah May 2014

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.

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Estimation And Testing In Type-Ii Generalized Half Logistic Distribution, R R. L. Kantam, V Ramakrishna, M S. Ravikumar May 2014

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.

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A Compound Of Geeta Distribution With Generalized Beta Distribution, Adil Rashid, T R. Jan May 2014

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.

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Hierarchical Clustering With Simple Matching And Joint Entropy Dissimilarity Measure, A Mete ÇilingtüRk, ÖZlem ErgüT May 2014

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, …

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An Exploratory Graphical Method For Identifying Associations In R X C Contingency Tables, Martin L. Lesser, Meredith B. Akerman May 2014

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.

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Separate Ratio-Type Estimators Of Population Mean In Stratified Random Sampling, Rajesh Tailor, Hilal A. Lone May 2014

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.

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Evaluation Of Area Under The Constant Shape Bi-Weibull Roc Curve, Sudesh Pundir, R Amala May 2014

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 …

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Investigating The Feasibility Of Using Mplus In The Estimation Of Growth Mixture Models, Ming Li, Jeffrey R. Harring, George B. Macready May 2014

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.

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A Reduced Bias Method Of Estimating Variance Components In Generalized Linear Mixed Models, Elizabeth A. Claassen May 2014

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 …

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Comparison Of Different Methods For Estimating Log-Normal Means, Qi Tang May 2014

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), …

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Nonparametric Identifiability Of Finite Mixture Models With Covariates For Estimating Error Rate Without A Gold Standard, Zheyu Wang, Xiao-Hua Zhou Apr 2014

Nonparametric Identifiability Of Finite Mixture Models With Covariates For Estimating Error Rate Without A Gold Standard, Zheyu Wang, Xiao-Hua Zhou

UW Biostatistics Working Paper Series

Finite mixture models provide a flexible framework to study unobserved entities and have arisen in many statistical applications. The flexibility of these models in adapting various complicated structures makes it crucial to establish model identifiability when applying them in practice to ensure study validity and interpretation. However, researches to establish the identifiability of finite mixture model are limited and are usually restricted to a few specific model configurations. Conditions for model identifiability in the general case have not been established. In this paper, we provide conditions for both local identifiability and global identifiability of a finite mixture model. The former …

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Asymmetric Empirical Similarity, Joshua C. Teitelbaum Mar 2014

Asymmetric Empirical Similarity, Joshua C. Teitelbaum

Georgetown Law Faculty Publications and Other Works

The paper offers a formal model of analogical legal reasoning and takes the model to data. Under the model, the outcome of a new case is a weighted average of the outcomes of prior cases. The weights capture precedential influence and depend on fact similarity (distance in fact space) and precedential authority (position in the judicial hierarchy). The empirical analysis suggests that the model is a plausible model for the time series of U.S. maritime salvage cases. Moreover, the results evince that prior cases decided by inferior courts have less influence than prior cases decided by superior courts.

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Adaptive Pair-Matching In The Search Trial And Estimation Of The Intervention Effect, Laura Balzer, Maya L. Petersen, Mark J. Van Der Laan Jan 2014

Adaptive Pair-Matching In The Search Trial And Estimation Of The Intervention Effect, Laura Balzer, Maya L. Petersen, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

In randomized trials, pair-matching is an intuitive design strategy to protect study validity and to potentially increase study power. In a common design, candidate units are identified, and their baseline characteristics used to create the best n/2 matched pairs. Within the resulting pairs, the intervention is randomized, and the outcomes measured at the end of follow-up. We consider this design to be adaptive, because the construction of the matched pairs depends on the baseline covariates of all candidate units. As consequence, the observed data cannot be considered as n/2 independent, identically distributed (i.i.d.) pairs of units, as current practice assumes. …

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Adaptive Randomized Trial Designs That Cannot Be Dominated By Any Standard Design At The Same Total Sample Size, Michael Rosenblum Jan 2014

Adaptive Randomized Trial Designs That Cannot Be Dominated By Any Standard Design At The Same Total Sample Size, Michael Rosenblum

Johns Hopkins University, Dept. of Biostatistics Working Papers

Prior work has shown that certain types of adaptive designs can always be dominated by a suitably chosen, standard, group sequential design. This applies to adaptive designs with rules for modifying the total sample size. A natural question is whether analogous results hold for other types of adaptive designs. We focus on adaptive enrichment designs, which involve preplanned rules for modifying enrollment criteria based on accrued data in a randomized trial. Such designs often involve multiple hypotheses, e.g., one for the total population and one for a predefined subpopulation, such as those with high disease severity at baseline. We fix …

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Meta-Analysis Of Social-Personality Psychological Research, Blair T. Johnson, Alice H. Eagly Jan 2014

Meta-Analysis Of Social-Personality Psychological Research, Blair T. Johnson, Alice H. Eagly

CHIP Documents

This publication provides a contemporary treatment of the subject of meta-analysis in relation to social-personality psychology. Meta-analysis literally refers to the statistical pooling of the results of independent studies on a given subject, although in practice it refers as well to other steps of research synthesis, including defining the question under investigation, gathering all available research reports, coding of information about the studies and their effects, and interpretation/dissemination of results. Discussed as well are the hallmarks of high-quality meta-analyses.

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Comparing K Population Means With No Assumption About The Variances, Tony Yaacoub Jan 2014

Comparing K Population Means With No Assumption About The Variances, Tony Yaacoub

College of Graduate Studies: Theses & Dissertations

In the analysis of most statistically designed experiments, it is common to assume equal variances along with the assumptions that the sample measurements are independent and normally distributed. Under these three assumptions, a likelihood ratio test is used to test for the difference in population means. Typically, the assumption of independence can be justified based on the sampling method used by the researcher. The likelihood ratio test is robust to the assumption of normality. However, the equality of variances is often difficult to justify. It has been found that the assumption of equal variances cannot be made even after transforming …

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Generalized Weibull And Inverse Weibull Distributions With Applications, Valeriia Sherina Jan 2014

Generalized Weibull And Inverse Weibull Distributions With Applications, Valeriia Sherina

College of Graduate Studies: Theses & Dissertations

In this thesis, new classes of Weibull and inverse Weibull distributions including the generalized new modified Weibull (GNMW), gamma-generalized inverse Weibull (GGIW), the weighted proportional inverse Weibull (WPIW) and inverse new modified Weibull (INMW) distributions are introduced. The GNMW contains several sub-models including the new modified Weibull (NMW), generalized modified Weibull (GMW), modified Weibull (MW), Weibull (W) and exponential (E) distributions, just to mention a few. The class of WPIW distributions contains several models such as: length-biased, hazard and reverse hazard proportional inverse Weibull, proportional inverse Weibull, inverse Weibull, inverse exponential, inverse Rayleigh, and Frechet distributions as special cases. Included …

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A General Procedure Of Estimating Population Mean Using Information On Auxiliary Attribute, Sachin Malik, Rajesh Singh, Florentin Smarandache Jan 2014

A General Procedure Of Estimating Population Mean Using Information On Auxiliary Attribute, Sachin Malik, Rajesh Singh, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

This paper deals with the problem of estimating the finite population mean when some information on auxiliary attribute is available. It is shown that the proposed estimator is more efficient than the usual mean estimator and other existing estimators. The results have been illustrated numerically by taking empirical population considered in the literature.

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Simulating Bipartite Networks To Reflect Uncertainty In Local Network Properties, Ravi Goyal, Joseph Blitzstein, Victor De Gruttola Dec 2013

Simulating Bipartite Networks To Reflect Uncertainty In Local Network Properties, Ravi Goyal, Joseph Blitzstein, Victor De Gruttola

Harvard University Biostatistics Working Paper Series

No abstract provided.

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Short-Term Inflation Forecasting Models For Nigeria, Sani I. Doguwa, Sarah O. Alade Dec 2013

Short-Term Inflation Forecasting Models For Nigeria, Sani I. Doguwa, Sarah O. Alade

CBN Journal of Applied Statistics (JAS)

Short-term inflation forecasting is an essential component of the monetary policy projections at the Central Bank of Nigeria. This paper proposes four short-term headline inflation forecasting models using the SARIMA and SARIMAX processes and compares their performance using the pseudo-out-of-sample forecasting procedure over July 2011 to September 2013. According to the results the best forecasting performance is demonstrated by the model based on the all items CPI estimated using the SARIMAX model. This model is, therefore, recommended for use in short-term forecasting of headline inflation in Nigeria. The forecasting performance up to eight months ahead, of the models based on …

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