Abstract
Time series analysis of Nigerian Inflation rate series is done. A seasonal difference and then a non-seasonal one were obtained. The correlogram of the differenced series revealed a seasonal nature. It also revealed a seasonal moving average component and a non-seasonal autoregressive component. $A (5,1,0)\times(0,1,1)_{12}$ seasonal model was fitted and shown to be adequate.
Highlights
A time series is defined as a set of data collected sequentially in time
The autocorrelation is a function of the lag separating the correlated values and called the autocorrelation function (ACF)
The inflation rate was calculated by Nigerian Inflation Rate Series (NINFR)(t) = [NCPT (t) − NCPI(t − 1)]/NCPI(t − 1)
Summary
A time series is defined as a set of data collected sequentially in time. It has the property that neighbouring values are correlated. A time series is said to be stationary if it has a constant mean and variance. The autocorrelation is a function of the lag separating the correlated values and called the autocorrelation function (ACF). A stationary time series {Xt} is said to follow an autoregressive moving average model of orders p and q (designated ARMA(p,q) if it satisfies the following difference
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