Modeling for COVID-19 Infections and Deaths in Tamil Nadu, India, Using Panel Regression Model | Chapter 11 | Research and Applications Towards Mathematics and Computer Science Vol. 7

 The impacts of the coronavirus ailment 2019 (COVID-19) pandemic have existed extremely severe, accompanying both business-related and health crises knowledgeable worldwide. The occurrence of novel COVID-19 infections dramatically raised due to the omission of antiviral medications and vaccines, resulting in colossal economic misfortunes, panic, and many deaths. Based on the committee regression model, this study checked the trends and correlations in the number of COVID-19-connected deaths and the number of COVID-19-polluted cases in all 37 regions of the Tamil Nadu state in India in Noble 2020. The fixed belongings model had the most excellent R2 profit of 78% and exhibited meaningful results. The slope coefficient was also well effective, appearance a considerable variation in the connection between new COVID-19 cases and afterlife. Additionally, for every whole increase in COVID-19-infected instances, the afterlife rate increased by 0.02%. The main issue with this model is that it acted not differentiate middle from two points the various districts or warn us whether the overall COVID-19 humanness response to the explanatory changing over time was constant across all neighborhoods.

Author(s) Details:

Rajarathinam Arunachalam,
Department of Statistics, Manonmaniam Sundaranar University, Tirunelveli-627 012, India.

Please see the link here: https://stm.bookpi.org/RATMCS-V7/article/view/12882

Statistical Modeling for Indian GDP, Export and Import | Chapter 6 | An Overview on Business, Management and Economics Research Vol. 3

 This branch investigates the relationship betwixt GDP, exports, and imports. The main objective of this phase is to resolve the dynamic links betwixt India's GDP, exports, and imports using dossier collected done yearly between 1950 and 2014. Gross household product (GDP) is a finances measure of the market profit of all the final merchandise and services presented in a specific an age by a country or countries. GDP is usually used apiece government of a distinct country to measure allure economic well-being. Due to its complex and emotional nature, this measure is frequently revised before being deliberate a reliable sign. The Jarque-Bera test (used to check for normality), the Augmented Dickey-Fuller part root test, the Phillips-Perron unit root test, the KPSS test (used to check for stationarity), and the Johansen Co-unification test (used to check for the number of con-integrating friendships among the latent variables) are among the miscellaneous econometrics tools. Vector Error Correction Model (to verify the variables' long-term friendships with one another) Both the Granger origin test and the Wald test have been used to decide the direction of origin. The stationarity test findings presented that the three variables under consideration have part roots at level I(0), but that they enhance stationary at level I(1) later being transformed into the first distinctness. The trace and Max-eigenvalue test statistics of Johansen’s Co-unification test indicated the life of two co-integrating equatings and exhibited a long-run evenness relationship betwixt the study variables. In the Vector Error Correction Model, C(1) is the coefficient of the mistake correction (co-unification) model, which is negative and important, indicating a long-run origin running from import and ship to GDP. The Wald test indicates that skilled are not around for long causalities running from export to GDP and no not around for long causality running from significance to GDP. The Granger Causality test reveals that bidirectional origin exists betwixt export and GDP and unidirectional origin between significance and GDP. The residuals on account of the Vector Error Correction Model are independent (no autocorrelation) and usually distributed. Also, the VECM model is empty Heteroskedasticity.

Author(s) Details:

Rajarathinam A.,
Department of Statistics, Manonmaniam Sundaranar University, Abishekapatti, Tirunelveli, Tamil Nadu, India.

Manikandan B.,
Department of Statistics, Manonmaniam Sundaranar University, Abishekapatti, Tirunelveli, Tamil Nadu, India.

Please see the link here: https://stm.bookpi.org/AOBMER-V3/article/view/12003

Statistical Modeling on COVID-19 Infected Cases and Deaths Based on Vector Auto-Regressive Model | Chapter 10 | An Overview on Business, Management and Economics Research Vol. 1

 The aim of this chapter search out use a panel heading auto-regressive model to imitate the dynamic equivalences between the number of COVID-19-infected sufferers and fatalities in all districts of Kerala state, India, from January 2021 to December 2021. Modeling vital relationships was appropriate for the haphazard effect panel vector automobile-regressive order two models. The inside variable, deaths (number of afterlife), is modeled to explain 62% of changes. Exogenous changeable deaths (-1) are very significant, whereas external variable cases (-1) are meaningful at a 5% level. The endogenous variable is absolutely impacted by both of these outside factors. The added external factors, extermination (-2) and cases (-2) are not statistically significant.

Author(s) Details:

A. Rajarathinam,
Manonmaniam Sundaranar University, Tirunelveli, Tamil Nadu, India.

Please see the link here: https://stm.bookpi.org/AOBMER-V1/article/view/11730