Open AccessModeling potato yield statistics by using information technology for sustainable development
Author(s) -
A P Darmanyan,
S I Bogdanov
Publication year - 2022
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/965/1/012058
Subject(s) - autocorrelation , statistics , autoregressive model , yield (engineering) , regression analysis , statistical model , econometrics , mathematics , linear regression , metallurgy , materials science
The potato yield statistics analysis and modeling in the Russian Federation according to the Federal State Statistics Service data for the period 2000-2020 was carried out. Based on the analysis of the autocorrelation function (Acf) as a mathematical model for modeling potato yield, the choice of a linear autoregressive model of the first order is justified. By using the multiple regression and correlation analysis methods, the parameters of the model were found, their statistical significance was proved, and the potato yield calculations proved the found model correspondence to real data for the period of 2002-2020.