Glance accepts a model object and returns a tibble::tibble()
with exactly one row of model summaries. The summaries are typically
goodness of fit measures, p-values for hypothesis tests on residuals,
or model convergence information.
Glance never returns information from the original call to the modelling function. This includes the name of the modelling function or any arguments passed to the modelling function.
Glance does not calculate summary measures. Rather, it farms out these
computations to appropriate methods and gathers the results together.
Sometimes a goodness of fit measure will be undefined. In these cases
the measure will be reported as NA
.
# S3 method for orcutt glance(x, ...)
x | An |
---|---|
... | Additional arguments. Not used. Needed to match generic
signature only. Cautionary note: Misspelled arguments will be
absorbed in |
glance()
, orcutt::cochrane.orcutt()
Other orcutt tidiers: tidy.orcutt
A tibble::tibble()
with exactly one row and columns:
Adjusted R squared statistic, which is like the R squared statistic except taking degrees of freedom into account.
Durbin-Watson statistic of original fit
Durbin-Watson statistic of transformed fit
Number of interactions
P-value of original Durbin-Watson statistic
P-value of autocorrelation after transformation
R squared statistic, or the percent of variation explained by the model. Also known as the coefficient of determination.
Spearman's rho autocorrelation
#> # A tibble: 4 x 5 #> term estimate std.error statistic p.value #> <chr> <dbl> <dbl> <dbl> <dbl> #> 1 (Intercept) 19.8 5.94 3.33 0.00244 #> 2 wt -5.03 1.22 -4.11 0.000310 #> 3 qsec 0.927 0.342 2.71 0.0114 #> 4 disp -0.000128 0.0106 -0.0121 0.990#> Cochrane-orcutt estimation for first order autocorrelation #> #> Call: #> lm(formula = mpg ~ wt + qsec + disp, data = mtcars) #> #> number of interaction: 7 #> rho 0.26819 #> #> Durbin-Watson statistic #> (original): 1.49575 , p-value: 4.063e-02 #> (transformed): 2.05696 , p-value: 5.21e-01 #> #> coefficients: #> (Intercept) wt qsec disp #> 21.814858 -4.852590 0.797029 -0.001359tidy(co)#> Warning: deal with tidy.orcutt conf.int nonsense#> # A tibble: 4 x 5 #> term estimate std.error statistic p.value #> <chr> <dbl> <dbl> <dbl> <dbl> #> 1 (Intercept) 21.8 6.63 3.29 0.00279 #> 2 wt -4.85 1.33 -3.65 0.00112 #> 3 qsec 0.797 0.370 2.15 0.0402 #> 4 disp -0.00136 0.0110 -0.123 0.903glance(co)#> # A tibble: 1 x 8 #> r.squared adj.r.squared rho number.interact… dw.original p.value.original #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 0.799 0.777 0.268 7 1.50 0.0406 #> # ... with 2 more variables: dw.transformed <dbl>, p.value.transformed <dbl>