scholarly journals Outdoor air pollution and infant mortality: analysis of daily time-series data in 10 English cities

2007 ◽  
Vol 61 (8) ◽  
pp. 719-722 ◽  
Author(s):  
S. Hajat ◽  
B. Armstrong ◽  
P. Wilkinson ◽  
A. Busby ◽  
H. Dolk
Keyword(s):  
Air Pollution ◽  
Time Series ◽  
Infant Mortality ◽  
Time Series Data ◽  
Series Data ◽  
Outdoor Air ◽  
Outdoor Air Pollution ◽  
Daily Time Series ◽  
Mortality Analysis ◽  
Daily Time

scholarly journals Modelling the Cumulative Number of COVID-19 Cases

2021 ◽  
Vol 02 (02) ◽  
pp. 1-1
Author(s):  
Mieczysław Szyszkowicz ◽  
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Distribution Functions ◽  
Cumulative Distribution ◽  
Series Data ◽  
Cumulative Number ◽  
Daily Time Series ◽  
Non Linear ◽  
The Usa ◽  
Daily Time

Each country has its own characteristics of COVID-19 infection trajectory and epidemic waves. Differences in government-implemented restrictions and social regulations result in variability of the virus transmissions and spread dynamics. This in turn results in various shapes of the growth function used to represent and describe the propagation of infection. Statistical methods are applied to fit non-linear functions to represent daily time-series data of the cumulative numbers of COVID-19 cases. The aim of this work is to fit various statistical models to the cumulative number of COVID-19 cases. Also to overview various types of the existed numerical methodologies. The data (since December 31, 2019) are available for almost each country in the world. As the examples, we used daily time-series data of the cumulative number of COVID-19 cases in Poland, Italy, Canada, and the USA. Non-linear approximations are applied to represent these time series data. The fitted functions allow us to investigate the dynamics of the pandemic. The constructed approximations are compositions of a few nonlinear functions, which describe the growth process of the COVID-19 infection trajectories. Two Gompertz functions and cumulative distribution functions (cdf) were estimated for the data of Poland and Italy (using the cdf for the normal distribution) and for the data of Canada and the USA (using the cdf for the gamma distribution). An analytical (parametric) functions representation of the number of COVID-19 cumulative cases is a useful tool to study the propagation of epidemics.

scholarly journals The Role of Human Capital Formation in Poverty Mitigation: A Co-integration Analysis from Pakistan

2016 ◽  
Vol 2 (2) ◽  
pp. 129-138
Author(s):  
Romaisa Arif ◽  
Muhammad Zahir Faridi ◽  
Fatima Farooq
Keyword(s):  
Higher Education ◽  
Time Series ◽  
Human Capital ◽  
Infant Mortality ◽  
Time Series Data ◽  
Capital Formation ◽  
Series Data ◽  
Human Capital Formation ◽  
Literacy Rate ◽  
Unit Change

The present study tries to explore the dynamic relationship between human capital formation and poverty mitigation by adopting the course of investment in education and health substances. For this sake, study takes heath expenditure and infant mortality rate as health indicators while status of education is captured with literacy rate and enrollment in higher education. Time series data is employed ranges from 1973-2013. The properties of time series data are inspected with the ADF test whilst PP test is employed for the robustness of unit root results. Mixed order of integration of data compels us to make use of ARDL technique for the estimation. Similarly, one unit change in health expenditures lead to reduce 0.251 units of poverty and one unit change in infant mortality cause to reduce poverty by 0.04 units. In last, one unit increase in literacy rate changes 1.03 units in poverty and one unit change in higher education results in 0.003 unit's change in poverty. The results of the study leave us with a clear finale for an optimal policy formulation that, Pakistan is in sturdy need of investment in health and education substances for a noteworthy accumulation of human capital for a right way poverty mitigation policy.

scholarly journals Short-term effects of ambient (outdoor) air pollution on cardiovascular death in Tehran, Iran – a time series study

Toxin Reviews ◽  
2019 ◽  
Vol 39 (2) ◽  
pp. 167-179
Author(s):  
Azizallah Dehghan ◽  
Narges Khanjani ◽  
Abbas Bahrampour ◽  
Gholamreza Goudarzi ◽  
Masoud Yunesian
Keyword(s):  
Air Pollution ◽  
Time Series ◽  
Cardiovascular Death ◽  
Outdoor Air ◽  
Short Term ◽  
Time Series Study ◽  
Outdoor Air Pollution ◽  
Series Study ◽  
Short Term Effects

Chaotic Identification of Hourly and Daily Water Level Time Series Data in Different Areas of Elevation at Pahang River

2021 ◽  
Vol 12 (3) ◽  
pp. 2427-2435
Author(s):  
Adib Mashuri Et.al
Keyword(s):  
Time Series ◽  
Phase Space ◽  
Water Level ◽  
Time Scale ◽  
Time Series Data ◽  
Phase Space Reconstruction ◽  
Series Data ◽  
Level Data ◽  
Water Level Data ◽  
Daily Time

This study focused on chaotic analysis of water level data in different elevations located in the highland and lowland areas. This research was conducted considering the uncertain water level caused by the river flow from highland to lowland areas. The analysis was conducted using the data collected from the four area stations along Pahang River on different time scales which were hourly and daily time series data. The resulted findings were relevant to be used by the local authorities in water resource management in these areas. Two methods were used for the analysis process which included Cao method and phase space plot. Both methods are based on phase space reconstruction that is referring to reconstruction of one dimensional data (water level data) to d-dimensional phase space in order to determine the dynamics of the system. The combination of parameters  and d is required in phase space reconstruction. Results showed that (i) the combination of phase space reconstruction’s parameters gave a higher value of parameters by using hourly time scale compared to daily time scale for different elevation; (ii) different elevation gave impact on the values of phase space reconstructions’ parameters; (iii) chaotic dynamics existed using Cao method and phase space plot for different elevation and time scale. Hence, water level data with different time scale from different elevation in Pahang River can be used in the development of prediction model based on chaos approach.

scholarly journals The Association between air pollution and COVID-19 related mortality in Santiago, Chile: A daily time series analysis

2021 ◽  
pp. 111284
Author(s):  
Robert Dales ◽  
Claudia Blanco-Vidal ◽  
Rafael Romero-Meza ◽  
Stephanie Schoen ◽  
Anna Lukina ◽  
...  
Keyword(s):  
Air Pollution ◽  
Time Series ◽  
Time Series Analysis ◽  
Series Analysis ◽  
Daily Time Series ◽  
Related Mortality ◽  
Daily Time
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