scholarly journals Estimation of the Number of Cumulative COVID-19 Cases by Day in Thailand Based on a Flattened Curve Policy

2021 ◽  
Vol 18 (13) ◽  
Author(s):  
Yupaporn AREEPONG ◽  
Rapin SUNTHORNWAT
Keyword(s):  
Growth Curve ◽  
Exponential Growth ◽  
Herd Immunity ◽  
Growth Curves ◽  
Least Square Method ◽  
Least Square ◽  
Coefficient Of Determination ◽  
Percentage Error ◽  
Logistic Growth ◽  
Thai Government

Since December 2019, the world has been facing an emerging infectious disease named coronavirus disease 2019. Thailand has also been affected by the spread of the coronavirus. The Thai government have announced policies to protect people, based on the emergency decree and curfew law for flattening the curve of the number of the coronavirus disease 2019 cases without vaccination in Thailand. This research estimated of the number of total infectious cases of coronavirus disease 2019 in Thailand. Two growth curves, including an exponential growth curve under a non-flattened curve policy (herd immunity policy without vaccination), and a logistic growth curve under a flattened curve policy without vaccination, were selected to estimate the parameters of the curves by the least square method to represent the number of the total infectious cases in Thailand. Moreover, the maximum infectious cases of coronavirus disease 2019 and the speed of spreading for coronavirus disease 2019 in Thailand were also explored. Based on the number of the total infectious cases of coronavirus disease 2019 in Thailand, the findings demonstrated that the coefficient of determination of the logistic growth curve was greater than the exponential growth curve and the root means squared percentage error of the logistic growth curve was less than the exponential growth curve. These results suggest that the logistic growth curve is suitable for describing the number of total infectious cases of coronavirus disease 2019 in Thailand under the fattened curve policy. GRAPHICAL ABSTRACT

scholarly journals Influence of Operating Parameters on Running-in Wear of EN-31 Steel

2016 ◽  
Vol 13 (1) ◽  
pp. 1-2
Author(s):  
M. Hanief ◽  
M. F. Wani
Keyword(s):  
Surface Roughness ◽  
Wear Rate ◽  
Least Square Method ◽  
Least Square ◽  
Coefficient Of Determination ◽  
Percentage Error ◽  
Model Parameters ◽  
Operating Parameters ◽  
Proposed Model ◽  
En 31

Abstract In this paper, effect of operating parameters (temperature, surface roughness and load) was investigated to determine the influence of each parameter on the wear rate. A mathematical model was developed to establish a functional relationship between the running-in wear rate and the operating parameters. The proposed model being non-linear, it was linearized by logarithmic transformation and the optimal values of model parameters were obtained by least square method. It was found that the surface roughness has significant effect on wear rate followed by load and temperature. The adequacy of the model was estimated by statistical methods (coefficient of determination (R2) and mean absolute percentage error (MAPE)) .

Effects of some factors on growth of lambs and the determination of growth curve models

2018 ◽  
Author(s):  
Ayhan Yilmaz ◽  
Ferda Karakus ◽  
Mehmet Bingöl ◽  
Baris Kaki ◽  
Gazel Ser
Keyword(s):  
Body Weight ◽  
Growth Curve ◽  
Growth Models ◽  
Age Groups ◽  
Growth Curves ◽  
The Body ◽  
Least Square ◽  
Coefficient Of Determination ◽  
Male And Female ◽  
Growth Curve Models

he aims were to identify the body weight of the several age groups in Norduz lambs and its correlations between these traits were to determine the best non-linear growth curve models for the growth performance of the Norduz sheep breed. A total of 91 male and female of Norduz lambs were evaluated under extensive system conditions. The least square means for weights at birth and at 15, 30, 45, 60, 75, 90, 105, 120, 135, 150, 165, 180, 195 and 210 days of age periods were 4.51±0.56, 9.28±0.25, 11.14±0.29, 14.99±0.37, 18.21±0.43, 22.54±0.54, 22.33±0.25, 23.59±0.54, 25.58±0.55, 28.07±0.58, 29.45±0.60, 29.98±0.84, 32.44±0.61, 32.03±0.59 and 31.45±0.57 kg, respectively. There were differences in favor of lambs of four-year old dams at 15 days of age and also lambs born single at 90 days of age for the body weight. The effect of weight of dam at birth, 30, 45, 60 days of age was significant (P less than 0.05-P less than 0.01) and the birth weight in lambs importantly effected the weights at 15, 30, and 45 days of age. All correlations between the body weights of several age periods were significant as statistical (P less than 0.01). As for the growth models, distinguished models were compared using the coefficient of determination and mean square error for both sexes. As a result, we concluded that von Bertalanffy model were the best model in comparison with the other models for biological growth curves in Norduz male and female lambs.

scholarly journals A Hybrid Modeling Technique of Epidemic Outbreaks with Application to COVID-19 Dynamics in West Africa

Biology ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 365
Author(s):  
Chénangnon Frédéric Tovissodé ◽  
Jonas Têlé Doumatè ◽  
Romain Glèlè Kakaï
Keyword(s):  
West Africa ◽  
Growth Curve ◽  
Exponential Growth ◽  
Latency Period ◽  
Growth Curves ◽  
Exponential Growth Phase ◽  
Model Framework ◽  
Logistic Regression Models ◽  
Containment Measures ◽  
Reporting Data

The widely used logistic model for epidemic case reporting data may be either restrictive or unrealistic in presence of containment measures when implemented after an epidemic outbreak. For flexibility in epidemic case reporting data modeling, we combined an exponential growth curve for the early epidemic phase with a flexible growth curve to account for the potential change in growth pattern after implementation of containment measures. We also fitted logistic regression models to recoveries and deaths from the confirmed positive cases. In addition, the growth curves were integrated into a SIQR (Susceptible, Infective, Quarantined, Recovered) model framework to provide an overview on the modeled epidemic wave. We focused on the estimation of: (1) the delay between the appearance of the first infectious case in the population and the outbreak (“epidemic latency period”); (2) the duration of the exponential growth phase; (3) the basic and the time-varying reproduction numbers; and (4) the peaks (time and size) in confirmed positive cases, active cases and new infections. The application of this approach to COVID-19 data from West Africa allowed discussion on the effectiveness of some containment measures implemented across the region.

scholarly journals A robust vector autoregressive model for forecasting economic growth in Malaysia

2018 ◽  
Vol 14 (3) ◽  
pp. 382-385
Author(s):  
Azme Khamis ◽  
Nur Azreen Abdul Razak ◽  
Mohd Asrul Affendi Abdullah
Keyword(s):  
Economic Growth ◽  
Least Square Method ◽  
Economic Indicator ◽  
Performance Measure ◽  
Least Square ◽  
Economic Indicators ◽  
Percentage Error ◽  
Monthly Basis ◽  
Vector Autoregressive ◽  
Auto Regressive

Economic indicator measures how solid or strong an economy of a country is. Basically, economic growth can be measured by using the economic indicators as they give an account of the quality or shortcoming of an economy. Vector Auto-regressive (VAR) method is commonly useful in forecasting the economic growth involving a bounteous of economic indicators. However, problems arise when its parameters are estimated using least square method which is very sensitive to the outliers existence. Thus, the aim of this study is to propose the best method in dealing with the outliers data so that the forecasting result is not biased. Data used in this study are the economic indicators monthly basis starting from January 1998 to January 2016. Two methods are considered, which are filtering technique via least median square (LMS), least trimmed square (LTS), least quartile difference (LQD) and imputation technique via mean and median. Using the mean absolute percentage error (MAPE) as the forecasting performance measure, this study concludes that Robust VAR with LQD filtering is a more appropriate model compare to others model. 

scholarly journals Delay Time Parameter and Its Confidence Interval of Predictive Time Series of COVID-19 Outbreak Between the First and the Second Wave

2021 ◽  
Vol 53 (2) ◽  
pp. 305-322
Author(s):  
Rapin Sunthornwat ◽  
Sirikanlaya Sookkhee
Keyword(s):  
Time Series ◽  
Confidence Interval ◽  
South Korea ◽  
Growth Curve ◽  
Delay Time ◽  
Time Parameter ◽  
Coefficient Of Determination ◽  
Percentage Error ◽  
The World ◽  
Second Wave

The outbreak of coronavirus disease 2019 (COVID-19) has become a major problem facing humans all around the world. For governments, in order to deal with the outbreak and protect the population, it is important to predict the number of infectious cases in the future to monitor the COVID-19 situation. This research aimed to compare the effectiveness of the logistic and the delay logistic time series in predicting the total number of infectious cases by using actual data from four countries, i.e. Thailand, South Korea, Egypt, and Nigeria. The total number of COVID-19 cases was collected during the first and the second wave of the COVID-19 outbreak. The validation and accuracy of the predictive growth curve time series were determined based on statistical values, i.e. the coefficient of determination and the root mean squared percentage error. It was found that the logistic time series was more appropriate for predicting the first wave in the four countries. For the second wave, the delay logistic time series was preferable. Moreover, the confidence interval based on Chebyshev’s inequality of delay time between the first and the second wave of the COVID-19 outbreak is also proposed.

scholarly journals Modeling on population growth and its adaptation: A comparative analysis between Bangladesh and India

2020 ◽  
Vol 12 (4) ◽  
pp. 688-701
Author(s):  
A.N.M. Rezaul Karim ◽  
Mohammed Nizam Uddin ◽  
Masud Rana ◽  
Mayeen Uddin Khandaker ◽  
M. R. I. Faruque ◽  
...  
Keyword(s):  
Population Growth ◽  
Growth Model ◽  
21St Century ◽  
Least Square Method ◽  
Exponential Model ◽  
The State ◽  
Least Square ◽  
Logistic Growth ◽  
Projection Data ◽  
Logistic Growth Model

The biggest challenge in the world is population growth and determining how society and the state adapt to it as it directly affects the fundamental human rights such as food, clothing, housing, education, medical care, etc. The population estimates of any country play an important role in making the right decision about socio-economic and population development projects. Unpredictable population growth can be a curse. The purpose of this research article is to compare the accuracy process and proximity of three mathematical model such as Malthusian or exponential growth model, Logistic growth model and Least Square model to make predictions about the population growth of Bangladesh and India at the end of 21st century. Based on the results, it has been observed that the population is expected to be 429.32(in million) in Bangladesh and 3768.53 (in million) in India by exponential model, 211.70(in million) in Bangladesh and 1712.94(in million) in India by logistic model and 309.28 (in million) in Bangladesh and 2686.30 (in million) in India by least square method at the end of 2100. It was found that the projection data from 2000 to 2020 using the Logistic Growth Model was very close to the actual data. From that point of view, it can be predicted that the population will be 212 million in Bangladesh and 1713 million in India at the end of the 21st century. Although transgender people are recognized as the third sex but their accurate statistics data is not available. The work also provides a comparative scenario of how the state has adapted to the growing population in the past and how they will adapt in the future.

scholarly journals A Hybrid Modelling Technique of Epidemic Outbreaks With Application to COVID-19 Dynamics in West Africa

2021 ◽  
Author(s):  
Chénangnon Frédéric Tovissodé ◽  
Jonas Têlé Doumatè ◽  
Romain Glèlè Kakaï
Keyword(s):  
West Africa ◽  
Growth Curve ◽  
Exponential Growth ◽  
Latency Period ◽  
Growth Curves ◽  
Exponential Growth Phase ◽  
Model Framework ◽  
Logistic Regression Models ◽  
Containment Measures ◽  
Reporting Data

The widely used logistic model for epidemic case reporting data may be either restrictive or unrealistic in presence of containment measures when implemented after an epidemic outbreak. For flexibility in epidemic case reporting data modelling, we combined an exponential growth curve for the early epidemic phase with a exible growth curve to account for the potential change in growth pattern after implementation of containment measures. We also fitted logistic regression models to recoveries and deaths from the confirmed positive cases. In addition, the growth curves were integrated in a SIQKU (Susceptible, Infective, Quarantined, Known recovered, Unknown recovered) model framework to provide an overview on the modelled epidemic wave. We focused on the estimation of: (1) the delay between the appearance of the first infectious case in the population and the outbreak ("epidemic latency period"); (2) the duration of the exponential growth phase; (3) the basic and the time-varying reproduction numbers; and (4) the peaks (time and size) in confirmed positive cases, active cases and new infections. The application of this approach to COVID-19 data from West Africa allowed to discuss the eectiveness of some containment measures implemented across the region.

scholarly journals Determinan Jumlah Uang Beredar, Tingkat Bunga, dan Inflasi Terhadap Pertumbuhan Ekonomi Indonesia

Al-Buhuts ◽  
2019 ◽  
Vol 15 (2) ◽  
pp. 45-64
Author(s):  
Adya Utami
Keyword(s):  
Economic Growth ◽  
Interest Rate ◽  
Money Supply ◽  
Negative Relationship ◽  
Secondary Data ◽  
Least Square Method ◽  
Least Square ◽  
Coefficient Of Determination ◽  
Independent Variable ◽  
The Interest Rate

This study aims to determine the determinants of the money supply, the interest rate, and inflation on Indonesia's economic growth in the 2009-2018 period. This research uses descriptive method and is strengthened by the OLS (ordinary least square) method with secondary data. The data used is sourced from the Central Statistics Agency and Bank Indonesia. The results of this study indicate that the money supply and the interest rate have a negative effect but inflation has a positive effect on Indonesia's economic growth. The JUB variable is not significant with a probability value of 0.1326. The JUB regression coefficient value has a negative relationship to the economic growth variable with a coefficient of 0.9288. The interest rate variable entered in the above equation turns out to be negative and significant with a probability value of 0.0571. The value of the coefficient of the exchange rate is (0.4843). The independent variable inflation gives a negative and not significant result with a probability value of 0.1134. Inflation coefficient value is 0.1724. In the equation model that uses economic growth as the dependent variable above, the magnitude of the coefficient of determination (R Squared) is 0.573429. This shows that the ability of the independent variable in explaining the diversity of the independent variables is 57.34% while the remaining 42.66% is influenced by other variables not included in the model.

Profitability of Tripura Gramin Bank and Regional Rural Bank in India: A comparison

GIS Business ◽  
2020 ◽  
Vol 15 (1) ◽  
pp. 313-330
Author(s):  
Puranjan Chakraborty ◽  
Dr. Ram Chandra Das
Keyword(s):  
Rural Areas ◽  
Secondary Data ◽  
Least Square Method ◽  
Financial Inclusion ◽  
Least Square ◽  
Annual Reports ◽  
Coefficient Of Determination ◽  
Socioeconomic Condition ◽  
Operating Profit ◽  
The Status

Tripura Gramin Bank (TGB) is the only Regional Rural Bank operating in Tripura since it’s inception in 1976. The bank was introduced for economic development of rural areas of Tripura. The prime objective of this bank was amelioration of socioeconomic condition of rural people of Tripura. The present study is an attempt to examine the status of the bank on profitability with an angle to look into financial inclusion in the state. Secondary data is used from the Annual Reports of TGB for the study period. Select parameters i.e. total income, total expenditure, non-interest income, operating expense, operating profit, net profit is used for the study. Select statistical tools i.e. CAGR, average, standard deviation, least square method; coefficient of determination is used to measure the status of profitability of TGB. The study reveals that, during the study period the profitability of TGB is improved which is the result of improvement of financial inclusion.

Relationship Between Two Stock–Recruitment Curves

1977 ◽  
Vol 34 (3) ◽  
pp. 425-428 ◽  
Author(s):  
L. L. Eberhardt
Keyword(s):  
Difference Equation ◽  
Population Growth ◽  
Population Size ◽  
Growth Curve ◽  
Population Biology ◽  
Population Regulation ◽  
Growth Curves ◽  
Equation Model ◽  
Logistic Growth ◽  
Stock Recruitment

The Beverton and Holt and Ricker stock–recruitment curves can be used to generate population growth curves. The Beverton and Holt curve is then identical to a difference equation model for the logistic growth curve, and may be derived in terms of equations for linearly density-dependent population regulation. The same equations lead to the Ricker curve if the density-regulating effect is assumed to depend only on population size at the beginning of the interval between generations. At low rates of population growth, the Ricker curve approaches that of Beverton and Holt. The two curves appear to represent certain concepts known in population biology as "r and K selection."

Sign in / Sign up

Export Citation Format

Share Document