Using a logistic growth regression model to forecast the demand for tourism in Las Vegas

2014 ◽  
Vol 12 ◽  
pp. 62-67 ◽  
Author(s):  
Fong-Lin Chu
Author(s):  
Milan Batista

AbstractIn the note, the logistic growth regression model is used for the estimation of the final size and its peak time of the coronavirus epidemic in China, South Korea, and the rest of the World.


2021 ◽  
Author(s):  
Mohamed LOUNIS ◽  
Babu Malavika

Abstract The novel Coronavirus respiratory disease 2019 (COVID-19) is still expanding through the world since it started in Wuhan (China) on December 2019 reporting a number of more than 84.4 millions cases and 1.8 millions deaths on January 3rd 2021.In this work and to forecast the COVID-19 cases in Algeria, we used two models: the logistic growth model and the polynomial regression model using data of COVID-19 cases reported by the Algerian ministry of health from February 25th to December 2nd, 2020. Results showed that the polynomial regression model fitted better the data of COVID-19 in Algeria the Logistic model. The first model estimated the number of cases on January, 19th 2021 at 387673 cases. This model could help the Algerian authorities in the fighting against this disease.


2020 ◽  
Author(s):  
Mohamed REZKI

In this paper, several techniques and models proposed the spread of coronavirus (Covid-19) and determines approximately the final number of coronavirus infected cases as well as infection point (peak time) in Algeria. To see the goodness of the predicting techniques, a comparative study was done by calculating error indicators such as Root-Mean-Square Error (RMSE) and the sum of squared estimate of errors (SSE). The main technique used in this study is the logistic growth regression model widely used in epidemiology. The results only relate to the two months from the beginning of the epidemic in Algeria, which should be readjusted by integrating the new data over time, because hazardous parameters like possible relaxations (decrease of vigilance or laxity of society) can affect these results and generally cause a time lag in the curve. Hence, a re-estimation of the curves is always requested.


10.1029/ft385 ◽  
1989 ◽  
Author(s):  
Christopher C. Barton ◽  
Paul A. Hsieh ◽  
Jacques Angelier ◽  
Francoise Bergerat ◽  
Catherine Bouroz ◽  
...  

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