BUSINESS ADMINISTRATION
BUSINESS ANALYTICS
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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use the average of the most recent data values in the time series as the forecast for the next period
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are used to smooth out random fluctuations in time series
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relate a time series to other variables that are believed to explain or cause its behavior
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occur whenever all the independent variables are previous values of the time series
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Detailed explanation-1: -Answer and Explanation: Autoregressive models occur whenever all the independent variables are previous values of the same time series since in an autoregressive model a value from the time series is regressed on previous values from the same time series.
Detailed explanation-2: -Autoregression is a time series model that uses observations from previous time steps as input to a regression equation to predict the value at the next time step. It is a very simple idea that can result in accurate forecasts on a range of time series problems.
Detailed explanation-3: -An AR(1) model may be estimated by placing the data series in two columns, but shifting one of the columns down by the number of rows corresponding to the desired lag. The original data series (unshifted) is the dependent variable and the shifted data series is the independent variable.
Detailed explanation-4: -Autoregressive models predict future values based on past values. They are widely used in technical analysis to forecast future security prices. Autoregressive models implicitly assume that the future will resemble the past.
Detailed explanation-5: -The only independent variable in time series methods is time.