These helpers provide the familiar S3 surface for mlxs_lm fits.
Usage
# S3 method for class 'mlxs_lm'
coef(object, ...)
# S3 method for class 'mlxs_lm'
predict(object, newdata = NULL, ...)
# S3 method for class 'mlxs_lm'
fitted(object, ...)
# S3 method for class 'mlxs_lm'
residuals(object, ...)
# S3 method for class 'mlxs_lm'
vcov(object, ...)
# S3 method for class 'mlxs_lm'
confint(object, parm, level = 0.95, ...)
# S3 method for class 'mlxs_lm'
anova(object, ...)
# S3 method for class 'mlxs_anova'
as.data.frame(x, row.names = NULL, optional = FALSE, ...)
# S3 method for class 'mlxs_anova'
print(x, ...)
# S3 method for class 'mlxs_anova'
tidy(x, ...)
# S3 method for class 'mlxs_lm'
summary(object, bootstrap = FALSE, bootstrap_args = list(), ...)
# S3 method for class 'mlxs_lm'
print(x, ...)
# S3 method for class 'summary.mlxs_lm'
print(x, ...)
# S3 method for class 'mlxs_lm'
model.frame(formula, ...)
# S3 method for class 'mlxs_lm'
model.matrix(object, ...)
# S3 method for class 'mlxs_lm'
terms(x, ...)
# S3 method for class 'mlxs_lm'
nobs(object, ...)
# S3 method for class 'mlxs_lm'
tidy(x, ...)
# S3 method for class 'mlxs_lm'
glance(x, ...)
# S3 method for class 'mlxs_lm'
augment(
x,
data = model.frame(x),
newdata = NULL,
se_fit = FALSE,
output = c("data.frame", "mlx"),
...
)Arguments
- object
An
mlxs_lmmodel fit.- ...
Additional arguments passed to underlying methods.
- newdata
Optional data frame for prediction.
- parm
Parameter specification for confidence intervals.
- level
Confidence level for intervals.
- x
An
mlxs_lmmodel fit (for methods with a leadingxargument).- row.names
Optional row names for data frame conversion.
- optional
Logical; passed to
as.data.frame.- bootstrap
Logical; should bootstrap standard errors be computed?
- bootstrap_args
List of bootstrap configuration options. See
mlxs_boot().- formula
An
mlxs_lmobject used in place of formula formodel.frame.- data
Optional data frame for
augment.- se_fit
Logical; should standard errors of fit be included?
- output
Character string; return format ("data.frame" or "mlx").