Default probabilities in a corporate bank portfolio: A logistic model approach

The COVID-19 pandemic impacted many socio-economic areas of countries around the world. It has made the production and business situations of enterprises face substantial difficulties. In this study, the authors used data envelopment analysis (DEA) models to assess the impact of the COVID-19 pandemic on Vietnam’s textile and garment enterprises. The authors have used the binary logistic model to determine the factors affecting employees’ decision to change jobs in the textile industry. The research results showed that the COVID-19 pandemic greatly affected the business performance of the textile and garment enterprises in Vietnam. Moreover, the results helped identify the factors affecting employee turnover and proposed solutions to help businesses stabilize their personnel situation and develop sustainable businesses in the post-COVID-19 era.

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Bivariate Response Logistic Regression for Categorical Data

NIGERIAN ANNALS OF PURE AND APPLIED SCIENCES ◽

10.46912/napas.122 ◽

2019 ◽

Vol 1 ◽

pp. 193-199

Author(s):

V Adah ◽

S C Nwaosu ◽

M E Nja

Keyword(s):

Logistic Regression ◽

Categorical Data ◽

Malaria Infection ◽

Logistic Model ◽

Joint Infection ◽

New Approach ◽

Explanatory Variables ◽

Joint Infections ◽

Bivariate Logistic Regression ◽

Model Approach

The bivariate logistic regression model can be used to obtain the probability of joint events as well as individual events where there are two response variables and several explanatory variables. The existing bivariate logistic model approach appears intractable. This paper provides a modeling procedure that addresses this problem. This approach compares favourably with the existing procedure. The new approach is used to model the probability of malaria and typhoid infections, using age, sex and location of the patients as associated factors. The marginal probabilities showed a decrease in malaria infection with age. Sex and location showed a significant impact on the probability of malaria infection. Typhoid fever infection on the other hand indicates an increase with age. Sex has no significant impact on the probability of typhoid infection. The joint model shows that all variables are statistically significant with odds value greater than 1 indicating higher likelihood of joint infection and odds value that are less than one indicating lower likelihood of joint infections, χ2:12.02828 (0.00729)

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LOGISTIC MODEL DEVELOPMENT FOR PREDICTION OF COVID-19 INFECTED INDIVIDUALS: CASE STUDY IN CENTRAL JAVA PROVINCE, INDONESIA

Journal of Fundamental Mathematics and Applications (JFMA) ◽

10.14710/jfma.v4i1.8385 ◽

2021 ◽

Vol 4 (1) ◽

pp. 96-103

Author(s):

Okky Widya Arditya ◽

Widowati Widowati ◽

Sutimin Sutimin ◽

R. Heru Tjahjana ◽

Priyo Sidik Sasongko

Keyword(s):

Logistic Model ◽

Model Development ◽

Dynamical Behaviour ◽

Central Java ◽

Contact Patterns ◽

High Death ◽

The Mathematical Model ◽

Central Java Province ◽

Model Approach

In early 2020, covid-19 spread fast in the worldwide and cause the high death. The disease started from the Asian region which resulted in a viral pandemic in 2020. In order to anticipate the increasing of the cases, a strategy is needed to inhibit its transmission. The mathematical model approach is important tool for predicting of covid-19 spread in populations. In this paper we propose and analyze the dynamical behaviour of a developed logistic model by considering the effect of the contact patterns in reducing the covid-19 spread process. To verify the developed logistic model, numerical simulation was given with case study of covid-19 spread for patients under supervision in Central Java Province, Indonesia. Based on simulation results, it was found that physical distancing can reduce the growth of the covid-19 spread for patient under supervision. It can be seen from the number of covid-19 spread for patients under supervision with physical distancing intervention smaller compared to without physical distancing intervention.

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