Open AccessCubic Spline Interpolation For Data Infections Of COVID-19 Pandemic In Iraq
Author(s) -
Jehan Mohammed Al-Ameri
Publication year - 2021
Publication title -
mağallaẗ al-qādisiyyaaẗ li-l-ʻulūm al-ṣirfaẗ
Language(s) - English
Resource type - Journals
eISSN - 2411-3514
pISSN - 1997-2490
DOI - 10.29350/qjps.2021.26.5.1443
Subject(s) - spline interpolation , covid-19 , spline (mechanical) , pandemic , interpolation (computer graphics) , monotone cubic interpolation , mathematics , statistics , econometrics , computer science , bicubic interpolation , medicine , infectious disease (medical specialty) , artificial intelligence , physics , bilinear interpolation , thermodynamics , motion (physics) , disease , pathology
In this paper, we use an empirical equation and cubic spline interpolation to fit Covid-19 data available for accumulated infections and deaths in Iraq. For Scientific visualization of data interpretation, it is useful to use interpolation methods for purposes fitting by data interpolation. The data used is from 3 January 2020 to 21 January 2021 in order to obtain graphs to analysing the rate of increasing the pandemic and then obtain predicted values for the data infections and deaths in that period of time. Stochastic fit to the data of daily infections and deaths of Covid-19 is also discussed and showed in figures. The results of the cubic splines and the empirical equation used will be numerically compared. The principle of least square errors will be used for both these interpolations. The numerical results will be indicated that the cubic spline gives an accurate fitting to data.