The analysis of partial autocorrelation function in predicting maximum wind speed

1st International Conference on Global Issue for Infrastructure, Environment & Socio-Economic Development

经济学;社会科学（总论）

Tinungki, G.M.^1

Department of Mathematics, Faculty of Mathematics and Natural Science, Hasanuddin University, Makassar

90245, Indonesia^1

关键词: Autocorrelation coefficient;    Autocorrelation functions;    Confidence interval;    Correlation measurement;    Expected values;    Maximum wind speed;    Partial autocorrelation;    Partial autocorrelation function;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/235/1/012097/pdf
DOI  :  10.1088/1755-1315/235/1/012097

学科分类：社会科学、人文和艺术（综合）

来源: IOP

【 摘 要 】

The stationary and non-stationary testing of the data set can be done using a plot analysis of the Partial Autocorrelation Function of the data, by viewing the maximum number of the expected value of Partial Autocorrelation. The Autocorrelation Function (ACF) is a function that shows the correlation between the observation of the t-time and the observation at the previous time. The autocorrelation function shows the autocorrelation coefficient, which is the correlation measurement of the observations at different times. Data taken from Statistics Indonesia -known in Indonesia as BPS (Badan Pusat Statistik)- contains the information about the maximum wind speed by month at the Paotere station in 2008 - 2017 in Makassar City. By using the data, the maximum wind speed for the next 12 months will be estimated.ie from January 2017 to December 2018. The results obtained, forecasting is done with 12 leads period ahead with 95% confidence interval.