001451613 000__ 06282cam\a2200613\a\4500
001451613 001__ 1451613
001451613 003__ OCoLC
001451613 005__ 20230310004709.0
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001451613 008__ 221203s2022\\\\sz\\\\\\o\\\\\101\0\eng\d
001451613 019__ $$a1352790271
001451613 020__ $$a9783031127786$$q(electronic bk.)
001451613 020__ $$a3031127781$$q(electronic bk.)
001451613 020__ $$z9783031127779
001451613 020__ $$z3031127773
001451613 0247_ $$a10.1007/978-3-031-12778-6$$2doi
001451613 035__ $$aSP(OCoLC)1352970190
001451613 040__ $$aEBLCP$$beng$$cEBLCP$$dGW5XE$$dYDX$$dOCLCF
001451613 049__ $$aISEA
001451613 050_4 $$aQA276.A1
001451613 08204 $$a519.5$$223/eng/20221213
001451613 1102_ $$aMexican Statistical Association.$$bMeeting$$d(2020 :$$cOnline)
001451613 24510 $$aInterdisciplinary statistics in Mexico :$$bAME virtual meeting, September 10-11, 2020, and 34 FNE, Acatlán, Mexico, September 22-24 2021, selected contributions /$$cIsadora Antoniano-Villalobos, Ruth Fuentes-García, Lizbeth Naranjo, Luis E. Nieto-Barajas, Silvia Ruiz-Velasco Acosta, editors.
001451613 260__ $$aCham :$$bSpringer,$$c2022.
001451613 300__ $$a1 online resource (234 p.).
001451613 4901_ $$aSpringer Proceedings in Mathematics and Statistics ;$$vv.397
001451613 500__ $$aSocial Lag in the Municipalities of the State of Guerrero, México
001451613 500__ $$aIncludes index.
001451613 5050_ $$aIntro -- Preface -- Contents -- A Methodological Proposal to Model and Evaluate the Complexity of the Mexican Geo-Electoral System -- 1 Introduction -- 2 Methodological Framework -- 2.1 Conceptualization of Electoral Complexity -- 2.2 Statistical Indicators for Quantifying Electoral Complexity -- 2.3 Data Transformation, Electoral Complexity Indices, and Stratification -- 3 ECI Construction and Stratification -- 3.1 Exploratory Analysis and PCA Implementation -- 3.2 Clustering Analysis and Stratification with K-Means -- 4 Electoral Complexity Ranking and Stratification Results
001451613 5058_ $$a5 Conclusions -- References -- A Spatial Analysis of Drug Dealing in Mexico City -- 1 Introduction -- 2 Background -- 2.1 Drug Dealing as Part of Organized Crime -- 2.2 Research Approaches -- 3 Methodology -- 4 Results -- 4.1 Univariate Global and Local Moran's I -- 4.2 Bivariate Global and Local Moran's I -- 5 Discussion and Conclusions -- References -- Bayesian Hierarchical Multinomial Modeling of the 2021 Mexican Election Outcomes with Censored Samples -- 1 Introduction -- 2 Background -- 2.1 Estimation Methods in the 2021 Quick Count -- 2.2 NBM Model Background -- 2.3 The Bias Problem
001451613 5058_ $$a3 The NBM Model -- 3.1 Specification -- 3.2 Consistency of Our Modeling Assumptions -- 3.3 Fitting Procedure -- 3.4 Model Adequacy -- 4 The 2021 Mexican Elections -- 4.1 Data and Sample Design -- 4.2 Results -- 5 Conclusions and Future Work -- References -- Assessing Hospitalization for SARS-CoV-2 Confirmed Cases by a Cross-Entropy Weighted Ensemble Classifier -- 1 Introduction -- 2 Material -- 2.1 Dataset Description -- 2.2 Data Analysis -- 3 Cross-entropy Weighted Ensemble Classifier -- 4 Results -- 5 Discussion -- 6 Conclusion -- References
001451613 5058_ $$aEmotion Analysis to Identify Risk of Committing Suicide Using Statistical Learning -- 1 Background -- 2 Materials and Methods -- 2.1 Emotion Mining -- 2.2 Statistical Learning Methods -- 2.3 Training and Test Datasets -- 3 Results -- 3.1 Supervised Models -- 3.2 Unsupervised Model -- 3.3 Model Comparison -- 3.4 Testing the Models with a New Test Set: COVID-19 -- 4 Conclusions -- References -- Characterizing Groups Using Latent Class Mixed Models: Antiretroviral Treatment Adherence Analysis -- 1 Introduction -- 2 Materials -- 2.1 Population -- 2.2 Data Collection -- 2.3 ART Adherence Definition
001451613 5058_ $$a3 Latent Class Mixture Models -- 4 Results -- 4.1 Latent Classes from ART Adherence -- 4.2 Latent Classes for Bivariate Response of CD4/CD8 Ratio and CD4+T Within Groups of Adherence -- 5 Discussion and Conclusions -- References -- A Dynamic Model for Analyzing the Public Health Policy of the Mexican Government During the COVID-19 Pandemic -- 1 Introduction -- 2 Related Work -- 3 Methods -- 3.1 SIRD Model -- 3.2 Transmission Rate Model -- 3.3 Recovery Rate Estimation -- 3.4 Bayesian Inference -- 4 Results -- 5 Conclusions -- References
001451613 506__ $$aAccess limited to authorized users.
001451613 520__ $$aThe volume includes a collection of peer-reviewed contributions from among those presented at the FNE, the main conference organized every two years by the Mexican Statistical Society (AME), and the 2020 AME Virtual Meeting. Statistical research in Latin America is prolific and research networks span both within and outside the region. As much of the work is typically carried out and published in Spanish, a large portion of the interested public is denied access to interesting findings, and the goal of this volume is therefore to provide access to selected works from Mexican collaborators and their international research networks to a wider audience. It may be especially attractive to academics interested in the latest methodological advances, while professionals from other disciplines may also find value in these new tools for data analysis. In 2021, the conference broadly focused on the interdisciplinary aspects of Statistics.
001451613 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed December 13, 2022).
001451613 650_0 $$aMathematical statistics$$vCongresses.
001451613 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772
001451613 655_0 $$aElectronic books.
001451613 7001_ $$aAntoniano-Villalobos, Isadora.
001451613 7001_ $$aFuentes-García, Ruth.
001451613 7001_ $$aNaranjo, Lizbeth.
001451613 7001_ $$aNieto-Barajas, Luis E.
001451613 7001_ $$aRuiz-Velasco Acosta, Silvia.
001451613 7112_ $$aForo Nacional de Estadística$$n(34th :$$d2021 :$$cOnline)
001451613 77608 $$iPrint version:$$aAntoniano-Villalobos, Isadora$$tInterdisciplinary Statistics in Mexico$$dCham : Springer International Publishing AG,c2023$$z9783031127779
001451613 830_0 $$aSpringer proceedings in mathematics & statistics ;$$vv. 397.
001451613 852__ $$bebk
001451613 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-12778-6$$zOnline Access$$91397441.1
001451613 909CO $$ooai:library.usi.edu:1451613$$pGLOBAL_SET
001451613 980__ $$aBIB
001451613 980__ $$aEBOOK
001451613 982__ $$aEbook
001451613 983__ $$aOnline
001451613 994__ $$a92$$bISE