- #FRONTLINE SOLVER LINEAR REGRESSION PREDICTION INTERVAL SOFTWARE#
- #FRONTLINE SOLVER LINEAR REGRESSION PREDICTION INTERVAL CODE#
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#FRONTLINE SOLVER LINEAR REGRESSION PREDICTION INTERVAL SOFTWARE#
Pred.int <- predict(model, interval = "prediction")
#FRONTLINE SOLVER LINEAR REGRESSION PREDICTION INTERVAL CODE#
The R code below creates a scatter plot with: Using a confidence interval when you should be using a prediction interval will greatly underestimate the uncertainty in a given predicted value (P. Generally, we are interested in specific individual predictions, so a prediction interval would be more appropriate. Which one should we use? The answer to this question depends on the context and the purpose of the analysis. Thus, a prediction interval will be generally much wider than a confidence interval for the same value. Prediction interval or confidence interval?Ī prediction interval reflects the uncertainty around a single value, while a confidence interval reflects the uncertainty around the mean prediction values.