A logistic regression approach for monthly rainfall forecasts in meteorological subdivisions of India based on DEMETER retrospective forecasts

2009 ◽  
Vol 30 (10) ◽  
pp. 1577-1588 ◽  
Author(s):  
K. Prasad ◽  
S. K. Dash ◽  
U. C. Mohanty
Keyword(s):  
Logistic Regression ◽  
Monthly Rainfall ◽  
Regression Approach

Using sellar region tumor’s size as a predictor of psychophysical and electrophysiological perimetric visual losses: a logistic regression approach

2019 ◽  
Vol 139 (3) ◽  
pp. 235-245
Author(s):  
Carlos Augusto Ferreira Lobão ◽  
Letícia Miquilini ◽  
Breno Simões Ribeiro da Silva ◽  
Verônica Gabriela Ribeiro da Silva ◽  
Eliza Maria da Costa Brito Lacerda ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Sellar Region ◽  
Regression Approach

scholarly journals Ranking of stroke and cardiovascular risk factors for an optimal risk calculator design: Logistic regression approach

2019 ◽  
Vol 108 ◽  
pp. 182-195 ◽  
Author(s):  
Elisa Cuadrado-Godia ◽  
Ankush D. Jamthikar ◽  
Deep Gupta ◽  
Narendra N. Khanna ◽  
Tadashi Araki ◽  
...  
Keyword(s):  
Risk Factors ◽  
Logistic Regression ◽  
Cardiovascular Risk ◽  
Cardiovascular Risk Factors ◽  
Risk Calculator ◽  
Regression Approach

scholarly journals The Determinants of Food Security among Households in Rangpur City, Bangladesh: A Logistic Regression Approach

2016 ◽  
Vol 07 (04) ◽  
pp. 51-56 ◽  
Author(s):  
Shahjahan Ali ◽  
Md. Thuhid Noor ◽  
Khandaker Jahangir Alam
Keyword(s):  
Logistic Regression ◽  
Food Security ◽  
Regression Approach

scholarly journals Determinants of return to work after maternity leave in Russia: A logistic regression approach

2020 ◽  
Vol 18 (3) ◽  
pp. 363-382
Author(s):  
Aleksandra K. Bordunos ◽  
◽  
Sofia V. Kosheleva ◽  
Anna Zyryanova ◽  
◽  
...  
Keyword(s):  
Logistic Regression ◽  
Return To Work ◽  
Maternity Leave ◽  
Personal Characteristics ◽  
Identity Work ◽  
Organizational Control ◽  
Work Identity ◽  
Gender And Work ◽  
Regression Approach ◽  
Returning To Work

This paper aims to identify the determinants of return to work after maternity leave in Russia. Can an organisation influence employees’ decision about withdrawal from the market after leave arrangement, or does it fully depend on the contextual and personal characteristics of the employee, as assumed by the discourses of merit and choice? Logistic regression analysis helps to answer the raised questions, referring to responses of 721 mothers with previous working experience. The research revealed that employers indeed can improve inclusion of employees with childcare commitments, fostering their return after the maternity leave. Despite high regional diversity of Russian population, contextual specificity barely influences the decision of employees regarding their returning to work with the same employer, similarly to their level of education, firms’ equity or amount of children. Among personal characteristics, income was found to play an important role in return decisions, as well as the age of the smallest child. The paper contributes to the debates on the fluidity of gender and work identity as well as organizational control over the identity work.

scholarly journals Determinants and Predictors of SMEs’ Financial Failure: A Logistic Regression Approach

Risks ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 107
Author(s):  
Youssef Zizi ◽  
Mohamed Oudgou ◽  
Abdeslam El Moudden
Keyword(s):  
Logistic Regression ◽  
Return On Assets ◽  
Classification Rate ◽  
Accounts Receivable ◽  
Financial Failure ◽  
Stepwise Method ◽  
Regression Approach ◽  
Asset Turnover ◽  
Duration Of Trade ◽  
One Year

This paper aims to identify the determinants and predictors of Small and Medium-sized Enterprises (SMEs)’ financial failure. Within this framework, we have opted for a quantitative method based on a sample of healthy and failing SMEs of a Moroccan bank. The main results of the different optimal models are obtained by the stepwise method of estimating logistic regression. These results show, in a normal economic context, that the variables that discriminate between healthy and failing SMEs are the main predictors of financial failure. Autonomy ratio, interest to sales, asset turnover, days in accounts receivable, and duration of trade payables are the variables that increase the probability of financial failure, while repayment capacity and return on assets reduce the probability of failure. These variables present an overall classification rate of healthy and failing SMEs of 91.11% three years before failure and of 84.44% two years and one year before failure.

scholarly journals A bayesian logistic regression approach to spoken language identification

2010 ◽  
Vol 7 (6) ◽  
pp. 390-396
Author(s):  
Haipeng Wang ◽  
Xiang Xiao ◽  
Xiang Zhang ◽  
Jianping Zhang ◽  
Yonghong Yan
Keyword(s):  
Logistic Regression ◽  
Spoken Language ◽  
Language Identification ◽  
Regression Approach ◽  
Bayesian Logistic Regression

A Multinomial Logistic Regression Approach for Arrhythmia Detection

2017 ◽  
Vol 8 (4) ◽  
pp. 17-33 ◽  
Author(s):  
Omar Behadada ◽  
Marcello Trovati ◽  
Georgios Kontonatsios ◽  
Yannis Korkontzelos
Keyword(s):  
Logistic Regression ◽  
Big Data ◽  
Multinomial Logistic Regression ◽  
Vascular Diseases ◽  
Arrhythmia Detection ◽  
Medical Sector ◽  
The World ◽  
Regression Approach ◽  
Insight Into ◽  
Tools And Methods

Cardiovascular diseases are the leading causes on mortality in the world. Consequently, tools and methods providing useful and applicable insights into their assessment play a crucial role in the prediction and managements of specific heart conditions. In this article, we introduce a method based on multi-class Logistic Regression as a classifier to provide a powerful and accurate insight into cardiac arrhythmia, which is one of the predictors of serious vascular diseases. As suggested by our evaluation, this provides a robust, scalable, and accurate system, which can successfully tackle the challenges posed by the utilisation of big data in the medical sector.

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