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Jon Anderson

Engin Sungur, Jon E. Anderson, Benjamin S. Winchester,   "Integration of Service-Learning Into Statistics Education." In Mathematics in Service to the Community: Concepts and Models for Service-Learning in the Mathematical Sciences, MAA Notes #66     pp.101-110:   The Mathematical Association of America, 2005

Abstract: We present ways in which we have improved our statistics curriculum by making connections with our community through service-learning projects.  We focus on three primary approaches:  course structure, course content, and bringing in outside contact and experiences.  Course structure aspects include course projects and assignments and the creation and integration of our Civic Engagement Workbook.  Under course content we present examples to illustrate learning objectives through a community connection.  Collaboration involves units both within and outside the university, the incorporation of consulting, and student feedback and reactions.

Link: http://www.amazon.com/Mathematics-Service-Community-Service-learning-Mathematical/dp/0883851768

Jong-Min Kim

Jong-Min Kim, and M.E. Elam, " A Two-Stage Stratified Warner's Randomized Response Model Using Optimal Allocation," in Metrika, Volume 61, pp 1-7, 2005

Abstract: This paper applies Kim and Warde's (2004) stratified Warner's randomized response model to Mangat and Singh's (1990) two-stage randomized response model. The proposed stratified randomized response model has an optimal allocation and a large gain in precision. Hence, the estimator based on the proposed method is more efficient than Kim and Warde's (2004) and Mangat and Singh's (1990) estimators under the conditions presented in both the case of completely truthful reporting and that of not completely truthful reporting by the respondents.

Link: http://cda.mrs.umn.edu/~jongmink/research/1840319.pdf

Jong-Min Kim, J. Tebbs and S.-W. An, "Extensions of Mangat's randomized-response model," in Journal of Statistical Planning and Inference, Volume 136, pp 1554-1567, 2006

Abstract: The randomized-response technique can be an effective survey method when collecting sensitive information. In this paper, we extend the model proposed by Mangat (J. Roy. Statist. Soc. Ser. B 56(1994) 93) in two ways. First, we propose a Bayesian version of the model, which is applicable when prior information on , the sensitive characteristic prevalence, is available. Our Bayesian approach can provide greatly-improved point estimators when compared to those obtained from maximum likelihood; furthermore, our approach provides estimators guaranteed to lie within the parameter space. Second, we extend Mangat's procedure to include data obtained from a stratified-sampling protocol and show that both of our new stratified procedures—one non-Bayesian and one Bayesian—are more efficient than the one initially proposed by Mangat (1994) for a single population.

Link: http://cda.mrs.umn.edu/~jongmink/research/paper4.pdf

Jong-Min Kim, and M.E. Elam, " A Stratified Unrelated Question Randomized Response Model," in Statistical Papers, Volume 48, pp 215-233, 2007

Abstract: This paper presents a new randomized response model that combines Kim and Warde's (2004) stratified Warner's randomized response technique using optimal allocation with the unrelated question randomized response model. The empirical studies performed show that, for the prior information given, the new model is more efficient in terms of variance (in the case of completely truthful reporting) and mean square error (in the case of less than completely truthful reporting) than its component models.

Link: http://cda.mrs.umn.edu/~jongmink/research/sp1.pdf

Engin Sungur, Jon E. Anderson, Benjamin S. Winchester,   "Integration of Service-Learning Into Statistics Education." In Mathematics in Service to the Community: Concepts and Models for Service-Learning in the Mathematical Sciences, MAA Notes #66     pp.101-110:   The Mathematical Association of America, 2005

Abstract: We present ways in which we have improved our statistics curriculum by making connections with our community through service-learning projects.  We focus on three primary approaches:  course structure, course content, and bringing in outside contact and experiences.  Course structure aspects include course projects and assignments and the creation and integration of our Civic Engagement Workbook.  Under course content we present examples to illustrate learning objectives through a community connection.  Collaboration involves units both within and outside the university, the incorporation of consulting, and student feedback and reactions.

Link: http://www.amazon.com/Mathematics-Service-Community-Service-learning-Mathematical/dp/0883851768

Engin Sungur

Jong-Min Kim, Engin A. Sungur, and T.-Y. Heo, " Calibration Approach Estimators in Stratified Sampling," in Statistics & Probability Letters, Volume 77, pp 99-103, 2007

ABSTRACT : Calibration is commonly used in survey sampling to include auxiliary information to increase the precision of the estimates of population parameter. In this paper, we newly propose various calibration approach ratio estimators and derive the estimator of the variance of the calibration approach ratio estimators in stratified sampling.
Link: http://cda.mrs.umn.edu/~jongmink/research/SPL2007.pdf

Jong-Min Kim, Y. Jung, E. A. Sungur, K. Han, C. Park, and I. Sohn, " A Copula Method for Modeling Directional Dependence of Genes," in BMC Bioinformatics, Volume 9, 225 pages, 2008

ABSTRACT : Genes interact with each other as basic building blocks of life, forming a complicated network. The relationship between groups of genes with different functions can be represented as gene networks. With the deposition of huge microarray data sets in public domains, study on gene networking is now possible. In recent years, there has been an increasing interest in the reconstruction of gene networks from gene expression data. Recent work includes linear models, Boolean network models, and Bayesian networks. Among them, Bayesian networks seem to be the most effective in constructing gene networks. A major problem with the Bayesian network approach is the excessive computational time. This problem is due to the interactive feature of the method that requires large search space. Since fitting a model by using the copulas does not require iterations, elicitation of the priors, and complicated calculations of posterior distributions, the need for reference to extensive search spa! ces can be eliminated leading to manageable computational affords. Bayesian network approach produces a discretely expression of conditional probabilities. Discreteness of the characteristics is not required in the copula approach which involves use of uniform representation of the continuous random variables. Our method is able to overcome the limitation of Bayesian network method for gene-gene interaction, i.e. information loss due to binary transformation.

Link: http://www.biomedcentral.com/1471-2105/9/225

Engin Sungur, "A Note on Directional Dependence in Regression Setting."   In Communications in Statistics--Theory and Methods: Regression Analysis, Volume 34, pp 1957-1965: Taylor and Francis, Inc, 2005  

ABSTRACT :   In this article, we define and study the concept of directional dependence in bivariate regression setting by using copulas. We consider two cases of directional dependence; one originating from marginals and the other originating from the joint behavior of variables. We also generalize and clarify the results given by Dodge and Rousson (2000) and Muddapur (2003).

Key words and phrases: Copulas; Regression function; Directional dependence; Correlation

Engin Sungur, "Regression Analysis Some Observations on Copula Regression Functions."   In Communications in Statistics--Theory and Methods: Regression Analysis , Volume 34: pp. 1967-1978, Taylor and Francis, Inc., 2005

ABSTRACT:   The main objective of this paper is to introduce an alternative way of looking at regression analysis by using copulas. To achieve our objective we work on copula regression function, study its properties, and discuss advantages that will come out from our approach.
 
KEY WORDS:  Copula; Regression; Conditional copula

Engin Sungur, Peh Ng, " A Decomposition of Copulas and Its Use." In Communications in Statistics--Theory and Methods: Regression Analysis, Volume ­­­­34, No. 12   pp. 2269-2282:   Taylor and Francis, Inc., 2005

ABSTRACT:   In this article, we create a decomposition that represents and describes the dependence structure between two variables. Since copulas provide a deep understanding of the dependence structure by eliminating the effects of the marginals, they play a key role in this study. We define a discretized copula density matrix and we decompose it into a set of permutation matrices by using the Birkhoff - von Neumann Theorem. This decomposition provides a way to effectively apply the concepts of copulas to solve problems in multivariate statistical data analysis.
 
KEY WORDS:  Birkhoff - von Neumann theorem, Copulas, Discretized copulas, Gini's measure, Permutation matrix, Doubly stochastic matrix, Prior probability.

Engin Sungur, Jon E. Anderson, Benjamin S. Winchester,   "Integration of Service-Learning Into Statistics Education." In Mathematics in Service to the Community: Concepts and Models for Service-Learning in the Mathematical Sciences, MAA Notes #66     pp.101-110:   The Mathematical Association of America, 2005

Abstract: We present ways in which we have improved our statistics curriculum by making connections with our community through service-learning projects.  We focus on three primary approaches:  course structure, course content, and bringing in outside contact and experiences.  Course structure aspects include course projects and assignments and the creation and integration of our Civic Engagement Workbook.  Under course content we present examples to illustrate learning objectives through a community connection.  Collaboration involves units both within and outside the university, the incorporation of consulting, and student feedback and reactions.

Link: http://www.amazon.com/Mathematics-Service-Community-Service-learning-Mathematical/dp/0883851768

 

Ben Winchester

Engin Sungur, Jon E. Anderson, Benjamin S. Winchester,   "Integration of Service-Learning Into Statistics Education." In Mathematics in Service to the Community: Concepts and Models for Service-Learning in the Mathematical Sciences, MAA Notes #66     pp.101-110:   The Mathematical Association of America, 2005

Abstract: We present ways in which we have improved our statistics curriculum by making connections with our community through service-learning projects.  We focus on three primary approaches:  course structure, course content, and bringing in outside contact and experiences.  Course structure aspects include course projects and assignments and the creation and integration of our Civic Engagement Workbook.  Under course content we present examples to illustrate learning objectives through a community connection.  Collaboration involves units both within and outside the university, the incorporation of consulting, and student feedback and reactions.

Link: http://www.amazon.com/Mathematics-Service-Community-Service-learning-Mathematical/dp/0883851768