Time Series Analysis and Forecast

Question 1

Autoregressive model

Answer 1

A regression model in which a regression relationship based on past time series values is used to predict the future time series values.

Question 2

Casual model

Answer 2

Forecasting method that relates a time series to other variables that are believed to explain or cause its behavior.

Question 3

Cyclical pattern

Answer 3

The component of the time series that results in periodic above-trend and below-trend behavior of the time series lasting more than one year.

Question 4

Exponential smoothing

Answer 4

A forecasting technique that uses a weighted average of past time series values as the forecast.

Question 5

Forecast

Answer 5

A prediction of future values in a time series

Question 6

Forecast error

Answer 6

The amount by which the forecasted value differs from the observed value

Question 7

Mean absolute error; mean absolute deviation

Answer 7

A measure of forecasting accuracy; the average of the values of the forecast errors.

Question 8

Mean absolute percentage error

Answer 8

A measure of the accuracy of a forecasting method; the average of the absolute values of the errors as a percentage of the corresponding forecast values.

Question 9

Mean squared error

Answer 9

A measure of the accuracy of a forecasting method; the average of the sum of the squared differences between the forecast values and the actual time series values.

Question 10

Moving averages method

Answer 10

A method of forecasting or smoothing a time series that uses the average of the most recent n data values in the time series as the forecast for the next period.

Question 11

Naive forecasting method

Answer 11

A forecasting technique that uses the value of the time series from the most recent period as the forecast for the current period.

Question 12

Seasonal pattern

Answer 12

The component of the time series that shows a periodic pattern over one year or less.

Question 13

Smoothing constant

Answer 13

A parameter of the exponential smoothing model that provides the weight given to the most recent time series value in the calculation of the forecast value.

Question 14

Stationary time series

Answer 14

A time series whose statistical properties are independent of time.

Question 15

Time series

Answer 15

A set of observations on a variable measured at successive points in time or over successive periods of time.

Question 16

Trend

Answer 16

The long-run shift or movement in the time series observable over several periods of time.