UTS Time Series 2023

What are the components of time series data, except?

• Trend

• Seasonal

• Cyclic

• Stationarity

Data IHK is an example of time series data with frequency?

• Daily

• Weekly

• Monthly

• Quarterly

What is the reason for the need for decomposition in time series data, except?

• Time series consists of 4 components

• Time series is influenced by seasonal factors

• Time series is influenced by trend

• Time series needs to be elaborated

Time series data with monthly frequency has seasonal (d) of:

• 1

• 4

• 6

• 12

Yt is a series with monthly frequency that is stationary in difference 1, has the following equation:

• D(Yt) = 0.2 + 0.05 D(Yt-1) + 0.15 D(Yt-2) - 0.2 et-12

• ARIMA(2,0,1)

• ARIMA(2,1,1)

• SARIMA (2,0,0)(0,0,1)12

• SARIMA (2,1,0)(0,0,1)12

The purpose of smoothing (data smoothing) methods is to:

• Eliminate or reduce random components

• Create decomposition of time series data

• Analyze changes of one variable against another

• Test data normality

Which of the following smoothing methods is not popular?

• Moving average

• Exponential smoothing

• Double exponential smoothing

• Multiple Linear Regression

The backshift operator notation for SARIMA(0,1,1)(0,1,1)4 is:

• (1-B)(1-B4)Yt =(1-θ1B)et

• (1-B)Yt =(1-θ1B)(1-θ1B4)et

• (1-B)(1-B4)Yt =(1-θ1B4)et

• (1-B)(1-B4)Yt =(1-θ1B)(1-θ1B4)et

If Yt has an ARIMA(1,0,0) model, which of the following statements is false?

• Series Yt is stationary at level

• Series Yt has an AR(1) model

• Yt = b0 + b1Yt-1 +et

• D(Yt) = b0 + b1D(Yt-1) +et

The difference between the Dicky Fuller Test (DF) and the Augmented Dicky Fuller Test (ADF) is:

• The error term in the random walk model in DF is assumed to have autocorrelation, while in ADF it does not

• The error term in the random walk model in DF is assumed not to have autocorrelation, while in ADF it has autocorrelation

• The error term in the random walk model in DF is assumed to have homogeneous variance, while in ADF it does not

• The error term in the random walk model in DF is assumed not to have homogeneous variance, while in ADF it has homogeneous variance