speedlm_tidiers {broom} | R Documentation |
These methods tidy the coefficients of a "speedlm" object into a summary, augment the original data with information on the fitted values and residuals, and construct a one-row glance of the model's statistics.
## S3 method for class 'speedlm' tidy(x, conf.int = FALSE, conf.level = 0.95, exponentiate = FALSE, quick = FALSE, ...) ## S3 method for class 'speedlm' glance(x, ...) ## S3 method for class 'speedlm' augment(x, data = stats::model.frame(x), newdata = data, ...)
x |
speedlm object |
conf.int |
whether to include a confidence interval |
conf.level |
confidence level of the interval, used only if
|
exponentiate |
whether to exponentiate the coefficient estimates and confidence intervals (typical for logistic regression) |
quick |
whether to compute a smaller and faster version, containing
only the |
... |
extra arguments (not used) |
data |
data frame to augment |
newdata |
new data to use for predictions, optional |
All tidying methods return a data.frame without rownames, whose structure depends on the method chosen.
tidy.speedlm
returns the tidied output of the
lm with one row for each term in the formula.
The columns match those in lm_tidiers.
glance.speedlm
returns a one-row data.frame with the columns
r.squared |
The percent of variance explained by the model |
adj.r.squared |
r.squared adjusted based on the degrees of freedom |
statistic |
F-statistic |
p.value |
p-value from the F test, describing whether the full regression is significant |
df |
Degrees of freedom used by the coefficients |
logLik |
the data's log-likelihood under the model |
AIC |
the Akaike Information Criterion |
BIC |
the Bayesian Information Criterion |
deviance |
deviance |
df.residual |
residual degrees of freedom |
augment.speedlm
returns one row for each observation, with just one column added:
.fitted |
Fitted values of model |
if (require("speedglm", quietly = TRUE)) { mod <- speedglm::speedlm(mpg ~ wt + qsec, data = mtcars) tidy(mod) glance(mod) augment(mod) }