Section 25 MLR: Prediction
Multiple Linear Regression: Prediction
25.1 Prediction from the model
\[ \large fm \leftarrow lm(SBP \sim BMI + Age, \space data=BP) \]
Confidence Interval
\[ \large predict(fm, \space newdata=X, \space se.fit=TRUE, \space interval=`confidence`) \]
Prediction Interval
\[ \large predict(fm, \space newdata=X, \space se.fit=TRUE, \space interval=`prediction`) \]
Call:
lm(formula = SBP ~ BMI + Age, data = BP)
Residuals:
Min 1Q Median 3Q Max
-8.6030 -2.0345 0.1196 1.9800 6.8630
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -10.83438 6.91013 -1.568 0.118
BMI 2.33147 0.07108 32.799 < 2e-16 ***
Age 1.09032 0.15678 6.954 1.12e-11 ***
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Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 2.633 on 497 degrees of freedom
Multiple R-squared: 0.8175, Adjusted R-squared: 0.8168
F-statistic: 1113 on 2 and 497 DF, p-value: < 2.2e-16