simple_eiv-methods: Methods for simple_eiv objects

Description

Methods defined for objects returned from error-in-variables models (e.g., dem_reg, pb_reg).

Usage

# S3 method for simple_eiv
print(x, ...)
# S3 method for simple_eiv
formula(x, ...)
# S3 method for simple_eiv
model.frame(formula, data = NULL, na.action = na.pass, ...)
# S3 method for simple_eiv
summary(object, ...)
# S3 method for simple_eiv
confint(object, parm, level = NULL, ...)
# S3 method for simple_eiv
plot(
  x,
  x_name = NULL,
  y_name = NULL,
  interval = c("none", "confidence"),
  level = NULL,
  n_points = 100,
  data = NULL,
  ...
)
# S3 method for simple_eiv
check(x, data = NULL, ...)
plot_joint(x, ...)
# S3 method for simple_eiv
plot_joint(
  x,
  ideal_slope = 1,
  ideal_intercept = 0,
  show_intervals = TRUE,
  n_points = 100,
  ...
)
# S3 method for simple_eiv
vcov(object, ...)
# S3 method for simple_eiv
coef(object, ...)
# S3 method for simple_eiv
fitted(object, type = c("y", "x", "both"), data = NULL, ...)
# S3 method for simple_eiv
residuals(object, type = c("optimized", "x", "y", "raw_y"), data = NULL, ...)
# S3 method for simple_eiv
predict(
  object,
  newdata = NULL,
  interval = c("none", "confidence"),
  level = NULL,
  se.fit = FALSE,
  data = NULL,
  ...
)

Value

print: Prints short summary of the EIV regression model.

summary

Prints detailed summary.

plot

Returns a plot of the regression line and data.

check

Returns plots of residuals.

plot_joint

Returns plot of joint confidence region (Deming only).

predict

Predicts Y values for new X values.

fitted

Extracts fitted values.

residuals

Extracts residuals.

coef

Extracts model coefficients.

vcov

Extracts variance-covariance matrix.

Arguments

...: further arguments passed through.
formula: A simple_eiv object (for model.frame method)
data: Optional data frame. Required if model was fitted with model = FALSE and newdata is NULL.
na.action: Function for handling NA values (default: na.pass)
object, x: object of class simple_eiv from dem_reg or pb_reg function.
parm: A specification of which parameters are to be given confidence intervals, either a vector of numbers or a vector of names. If missing, all parameters are considered.
level: Confidence level for intervals (default uses the model's conf.level).
x_name: Name for x-axis label (optional).
y_name: Name for y-axis label (optional).
interval: Type of interval calculation. Can be "none" (default), or "confidence"
n_points: Number of points to use for drawing the joint confidence region (default = 100).
ideal_slope: The hypothesized slope value to test against (default = 1)
ideal_intercept: The hypothesized intercept value to test against (default = 0)
show_intervals: Logical. If TRUE, shows individual confidence intervals as well.
type: Type of residuals to return. Options are "optimized" (default), "x", "y", or "raw_y".
newdata: An optional data frame containing values of X at which to predict. If omitted, the fitted values are returned.
se.fit: Logical. If TRUE, standard errors of predictions are returned. Note: For Passing-Bablok regression without bootstrap, standard errors are not available and this argument is ignored with a warning.