1,720,957 research outputs found
Kernel Nonparametric Regression Modeling with the Nadaraya-Watson Estimator (Case Study: Fertility in the Southern Sumatra Region)
Get PDFFertility is a live birth, namely the release of a baby from a woman\u27s womb with signs of life such as screaming, breathing, a throbbing heart, and so on. The source of this research data comes from the publication of the official website of the Central Statistics Agency (BPS). This study aims to model and predict fertility data in 2020 with kernel nonparametric regression using the Nadaraya-Watson estimator. The nonparametric kernel model shows the relationship between fertility (Y) and the percentage of underage women at first marriage , the percentage of women 15-49 years who do not use traditional KB or conventional methods , the number of active family planning participants , the number of couples of childbearing age , the percentage of the average length of schooling , and the total expenditure per capita based on Gaussian kernel function and bandwidth values. Based on the results of the analysis, the independent variables that have a significant effect are , , , on the dependent variable with the optimum bandwidth value of 0.490 and the value of R2 of 99.6%, and the MSE value of 0.332. Modeling fertility is important as it helps understand and predict population trends. It provides insights into the potential number of births in a population in the future. This information can be used for policy planning, including health, educations, and social policies
Survival Analysis of Students Not Graduated on Time Using Cox Proportional Hazard Regression Method and Random Survival Forest Method
Get PDFHigher education is a place to educate the next generation of the nation in terms of academic and non-academic. Basically every college tries to maximize the graduation of its students, both in quantity and quality. The undergraduate education program is targeted to complete 8 semesters of study or can also be taken in less than 8 semesters and a maximum of 14 semesters. Many factors are thought to affect the length of student study, both internal and external factors. Based on the factors that are thought to affect the length of study of the student, it is necessary to conduct research to determine what factors have a significant effect on the length of study of the student. The method that can be used to determine these factors is survival analysis using cox proportional hazard regression and random survival forest. Factors that affect the length of study using cox proportional hazard regression is GPA, while by using the random survival forest method, the factors that influence the length of study of students are GPA, gender, and part time. Based on the comparison using the C-Index method, random survival forest is a suitable method to use in the data because the C-Index error value is 26.9% which is smaller than the cox proportional hazard which is 27.8%
MODELING THE MANY EARTHQUAKES IN SUMATRA USING POISSON HIDDEN MARKOV MODELS AND EXPECTATION MAXIMIZATION ALGORITHM
Get PDFSumatra Island is one of the islands that are prone to earthquakes because Sumatra Island is located at the confluence of three plates, namely the large Indo-Australian plate, the Eurasian plate and the Philippine plate. In general, the number of earthquake events follows the Poisson distribution, but there are cases where there is overdispersion in the Poisson distribution. The Poisson Hidden Markov Models (PHMMs) method is used to overcome overdispersion, then applying the Expectation-Maximization Algorithm (EM algorithm) to each model to obtain the estimated parameters. From the models obtained, the best model will be selected based on the smallest Akaike Information Criterion (AIC) value. The data used is secondary data on earthquake events on the island of Sumatra from January 2000 to December 2022 with a depth of ≤ 70 Km and a magnitude of ≥ 4.4 Mw. From the research, the model with m = 3 is the best estimation model with an AIC value of 1503,286. From the best model, estimates are obtained for Poisson Hidden Markov Models with an average occurrence of earthquakes of 5.7633 ≈ 6 events within one month
Comparison of Geographically Weighted Generalized Poisson Regression (GWGPR) and Geographically Weighted Negative Binomial Regression (GWNBR) Methods in Determining Factors Affecting Tuberculosis Cases in Indonesia
Get PDFThe findings of this study demonstrate that both the Geographically Weighted Generalized Poisson Regression (GWGPR) and Geographically Weighted Negative Binomial Regression (GWNBR) models are effective in modeling tuberculosis (TB) incidence data characterized by overdispersion and spatial heterogeneity. Although both models yield comparable fit statistics—as indicated by nearly identical Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) values—GWGPR exhibits a higher sensitivity to regional variability, as evidenced by the formation of four distinct provincial clusters based on significant predictor variables, compared to only two clusters identified by the GWNBR model. This suggests that GWGPR may offer a more nuanced understanding of spatial effects in epidemiological data. Furthermore, several covariates; namely smoking prevalence, average annual humidity, number of rainy days, reported health complaints, and TB case detection and treatment coverage, emerged as consistently significant across all provinces in both modeling approaches. The recurrence of these variables across spatially disaggregated models highlights their fundamental role in influencing TB transmission dynamics at a national scale. Accordingly, the use of spatially adaptive models such as GWGPR can support more targeted and effective disease control strategies by aligning health policy responses with the localized determinants of TB burden
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
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