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Alternative Methodology of Location Model for Handling Outliers and Empty Cells Problems: Winsorized Smoothed Location Model
Get PDFThe location model is a familiar basis for discrimination dealing with mixed binary and continuous variables simultaneously. The binary variables create cells while the continuous variables are information that measures the difference between groups in each cell. But, if some of the created cells are empty, the classical location model rule is biased and sometimes infeasible. Interestingly, the analyses of previous studies have revealed that non-parametric smoothing approach succeeded in reducing the effects of some empty cells immensely. However, one practical drawback to the use of discrimination methods based on the location model is that the smoothing approach employed, its performance is severe when there are outliers in the data sample. The purpose of this paper is to extend these limitations of the location model with the presence of outliers and empty cells. Accordingly, a new location model rule called Winsorized smoothed location model is developed through the combination of Winsorization and non-parametric smoothing approach to address both issues of outliers and empty cells at once. Results from simulation manifests the improvement of the new rule as the rates of misclassification are dramatically declined even the data contains outliers for all 36 different simulation data settings. Findings from real dataset, full breast cancer, also clearly show that the newly developed Winsorized smoothed location model achieves the best performance compared to over than 10 existing discrimination methods. These revealed that the newly derived rule further enhanced the applicability range of the location model, as previously it was limited to the non-contaminated datasets to achieve tolerable performance. The overall investigation verifying the new rule developed offers practitioners another potential good methodology for discrimination tasks, as the rule very favourably compared to all its competitors except only on
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Get PDFWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Get PDFWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
Markov chain in modeling Universiti Utara Malaysia undergraduate student
Get PDFIn this study, we have used Markov chain to model the flow of full time undergraduate students in Universiti Utara Malaysia (UUM) of 2003 and 2004.Through this model, we have estimated the probability of a student to complete a course and the mean times it take to complete it distinguished by age, gender, programme undertaken and the minimum entrance qualification used in enrolling at UUM
A new approach for classifying large number of mixed variables
Get PDFThe issue of classifying objects into one of predefined
groups when the measured variables are mixed with different types of variables has been part of interest among statisticians in many years. Some methods for dealing with such situation have been introduced that include parametric, semi-parametric and non-parametric approaches. This paper attempts to discuss on a problem in classifying a data when the number of measured mixed variables is
larger than the size of the sample.A propose idea that integrates a dimensionality reduction technique via principal component analysis and a discriminant function based on the location model is discussed. The study aims in offering practitioners another potential tool in a classification problem that is possible to be considered when the observed variables are mixed and too large
New Location Model Based on Automatic Trimming and Smoothing Approaches
No full textLocation Model is a classification approach that capable to deal with mixed binary and continuous variables at once.The binary variables create segmentation in the groups called cells whilst the continuous variables measure the differences between groups based on information inside the cells.It is important to note that location model is biased and even impossible to be constructed when involving some empty cells.Interestingly from previous studies, smoothing approach managed to remedy the effects of some empty cells.However, numerical analysis has demonstrated that the performances of the location model based on smoothing approach are good in most situations except if there are outliers in the sample.Thus, the presence of outliers has alarmed us to further investigating the performance of the location model.Therefore, in this paper, we develop a new methodology of location model producing new model called automatic trimmed location model through new estimators resulting from an integration of automatic trimming and smoothing approaches in addressing both issues of outliers and empty cells simultaneously.The results have confirmed that the new methodology developed as well as the new location model produced offer another potential tools to practitioners, which possible to be considered in classification problems when the data samples contain outliers and at the same time could resolve the crisis of some empty cells of the location model. Copyrigh
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