search for: mlm2

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2012 Mar 16
1
multivariate regression and lm()
...0.4286 z1 2.0000 0.4472 4.472 0.0208 * --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 1.414 on 3 degrees of freedom Multiple R-squared: 0.8696, Adjusted R-squared: 0.8261 F-statistic: 20 on 1 and 3 DF, p-value: 0.02084 > f.mlm2 = lm(y2 ~ z1, data=ex7.8); summary(f.mlm2) Call: lm(formula = y2 ~ z1, data = ex7.8) Residuals: 1 2 3 4 5 -1.110e-16 -1.000e+00 1.000e+00 1.000e+00 -1.000e+00 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -1.0000...