Application of Autoregressive Integrated Moving Average Model and Weighted Markov Chains on Forecasting Under-Five Mortality Rates in Nigeria
نویسندگان
چکیده
The aim of this paper is to obtain the best model that will be used predict Under-Five Mortality Rate (U5MR) between Autoregressive Integrated Moving Average (ARIMA) and Weighted Markov Chains (WMC). annual dataset U5MR in Nigeria for period 1980-2019 obtained from official website World Bank. descriptive statistics unit root test stationarity data were carried on series. ARIMA was modelled using techniques Box-Jenkins while WMC k-means cluster analysis, Chi-Square, Correlation. Bayesian Information Criterion (BIC) forecast Theil’s U Statistics Mean Absolute Percentage Error (MAPE). attained after third differencing under dynamics. ARIMA(0,3,2) considered with BIC -2.679, selected as Statistic 0.000014 MAPE 0.174336%. fitted make out-sample 2020-2030, which showed a steady decline. findings help establishment implementation health policies.
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ژورنال
عنوان ژورنال: Asian Journal of Probability and Statistics
سال: 2022
ISSN: ['2582-0230']
DOI: https://doi.org/10.9734/ajpas/2022/v16i130393