Returns the coefficient table (estimate, standard error, t value, p value), the residual standard error, R-squared and adjusted R-squared, and the overall F-statistic.
Arguments
- object
An object of class
"ols".- robust
Heteroscedasticity-consistent covariance for the standard errors and t / F tests.
"none"(default) uses the classical covariance;"HC0"-"HC3"use a sandwich estimator.- ...
Currently ignored.
- x
A
summary.olsobject.- digits
Significant digits for numeric output.
Examples
fit <- ols(mpg ~ wt + hp, data = mtcars)
summary(fit)
#> Call:
#> ols.formula(x = mpg ~ wt + hp, data = mtcars)
#>
#> linear model (OLS)
#>
#> Coefficients:
#> Estimate Std. Error t value Pr(>|t|)
#> (Intercept) 37.22727 1.59879 23.285 < 2e-16 ***
#> wt -3.87783 0.63273 -6.129 1.12e-06 ***
#> hp -0.03177 0.00903 -3.519 0.00145 **
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#>
#> Residual standard error: 2.593 on 29 degrees of freedom
#> Multiple R-squared: 0.8268, Adjusted R-squared: 0.8148
#> F-statistic: 69.21 on 2 and 29 DF, p-value: 9.109e-12
summary(fit, robust = "HC3")
#> Call:
#> ols.formula(x = mpg ~ wt + hp, data = mtcars)
#>
#> linear model (OLS) -- HC3 robust standard errors
#>
#> Coefficients:
#> Estimate Std. Error t value Pr(>|t|)
#> (Intercept) 37.227270 2.229805 16.695 < 2e-16 ***
#> wt -3.877831 0.768519 -5.046 2.23e-05 ***
#> hp -0.031773 0.009385 -3.385 0.00206 **
#> ---
#> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#>
#> Residual standard error: 2.593 on 29 degrees of freedom
#> Multiple R-squared: 0.8268, Adjusted R-squared: 0.8148
#> F-statistic: 35.73 on 2 and 29 DF, p-value: 1.499e-08