mlxs_glm method utilities

Support functions that provide a familiar S3 surface for mlxs_glm fits by delegating to equivalent base glm behaviour where helpful.

Usage

# S3 method for class 'mlxs_glm'
weights(object, type = c("prior", "working"), ...)

# S3 method for class 'mlxs_glm'
predict(
  object,
  newdata = NULL,
  type = c("link", "response"),
  se.fit = FALSE,
  ...
)

# S3 method for class 'mlxs_glm'
fitted(object, ...)

# S3 method for class 'mlxs_glm'
residuals(object, type = c("deviance", "pearson", "working", "response"), ...)

# S3 method for class 'mlxs_glm'
vcov(object, ...)

# S3 method for class 'mlxs_glm'
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_glm'
print(x, digits = max(3, getOption("digits") - 3), ...)

# S3 method for class 'mlxs_glm'
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 'summary.mlxs_glm'
print(x, digits = max(3, getOption("digits") - 3), ...)

# S3 method for class 'mlxs_glm'
anova(object, ...)

# S3 method for class 'mlxs_glm'
model.frame(formula, ...)

# S3 method for class 'mlxs_glm'
model.matrix(object, ...)

# S3 method for class 'mlxs_glm'
terms(x, ...)

# S3 method for class 'mlxs_glm'
nobs(object, ...)

# S3 method for class 'mlxs_glm'
tidy(x, ...)

# S3 method for class 'mlxs_glm'
glance(x, ...)

# S3 method for class 'mlxs_glm'
augment(
  x,
  data = x$model,
  newdata = NULL,
  type.predict = c("response", "link"),
  type.residuals = c("response", "deviance"),
  se_fit = FALSE,
  output = c("data.frame", "mlx"),
  ...
)

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

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

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

Arguments

object, model

An mlxs_glm model fit.

type

Character string indicating the scale of the prediction or residuals to return.

...

Additional arguments passed to underlying methods.

newdata

Optional data frame used for prediction.

se.fit

Logical. Should standard errors of the fit be returned when supported?

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

digits

Number of significant digits to print for summaries.

confint

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

formula, data

Optional formula and data overrides used by augment.mlxs_glm().

type.predict, type.residuals

Character strings controlling the scale of fitted values and residuals returned by augment.mlxs_glm().

se_fit

Logical; standard-error analogue for augment.

output

Character string; return format ("data.frame" or "mlx").