mlxs_lm method utilities

These helpers provide the familiar S3 surface for mlxs_lm fits.

Usage

# 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,
  ...,
  bootstrap = FALSE,
  bootstrap_args = list(B = 200L, seed = NULL, progress = FALSE, bootstrap_type = "case")
)

# 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(B = 200L, seed = NULL, progress = FALSE, bootstrap_type = "case"),
  confint = FALSE,
  level = 0.95,
  ...
)

# 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"),
  ...
)

# S3 method for class 'mlxs_lm'
estfun(x, ..., output = c("matrix", "mlx"))

# S3 method for class 'mlxs_lm'
hatvalues(model, ..., output = c("matrix", "mlx"))

# S3 method for class 'mlxs_lm'
bread(x, ...)

Arguments

object, model

An mlxs_lm model fit.

newdata

Optional data frame for prediction.

...

Additional arguments passed to underlying methods.

parm

Parameter specification for confidence intervals.

level

Confidence level for intervals.

bootstrap

Logical; should bootstrap standard errors or confidence intervals be computed?

bootstrap_args

List of bootstrap configuration options. See mlxs_boot().

x

An mlxs_lm model fit (for methods with a leading x argument).

row.names

Optional row names for data frame conversion.

optional

Logical; passed to as.data.frame.

confint

Logical; should confidence intervals be included in the summary object?

formula

An mlxs_lm object used in place of formula for model.frame.

data

Optional data frame for augment.

se_fit

Logical; should standard errors of fit be included?

output

Character string; return format ("data.frame", "matrix", "vector" or "mlx"). To make methods from other packages work, the usual default is to return a base R object.