Learn how ARIMA models use time series data for accurate short-term forecasting. Discover its pros, cons, and essential tips ...

Using Linear Regression Because much economic data has cycles, multiple trends and non-linearity, simple linear regression is often inappropriate for time-series work, according to Yale University.

J. B. Copas, Regression, Prediction and Shrinkage, Journal of the Royal Statistical Society. Series B (Methodological), Vol. 45, No. 3 (1983), pp. 311-354 ...

The four main methods are straight line forecasting, moving average forecasting, simple linear regression forecasting and multiple linear regression forecasting.

A Two-Stage Forecasting Model: Exponential Smoothing and Multiple Regression By: D. B. Crane and James R. Crotty Format: Print ...

Multiple Linear Regression In linear regression, when there's just a single independent variable, the analysis is sometimes called simple linear regression to distinguish the analysis from situations ...

The literature of regression analysis with missing values of the independent variables is reviewed. Six classes of procedures are distinguished: complete case analysis, available case methods, least ...

Using historical data and regression analysis has its limitations in business forecasting. For example, a significant correlation between the independent and dependent variable does not ...