Delta Method (Generic Object Input)

Calculates delta method sampling variance-covariance matrix for a function of parameters using a numerical Jacobian.

Usage

DeltaGeneric(
  object,
  def,
  theta = 0,
  alpha = c(0.05, 0.01, 0.001),
  z = TRUE,
  df = NULL
)

Arguments

object

R object. Fitted model object with coef and vcov methods that return a named vector of estimated parameters and sampling variance-covariance matrix, respectively.

def

List of character strings. A list of defined functions of parameters. The string should be a valid R expression when parsed and should result a single value when evaluated.

theta

Numeric vector. Parameter values when the null hypothesis is true.

alpha

Numeric vector. Significance level/s.

z

Logical. If z = TRUE, use the standard normal distribution. If z = FALSE, use the t distribution.

df

Numeric. Degrees of freedom if z = FALSE.

Value

Returns an object of class deltamethod which is a list with the following elements:

call

Function call.

args

Function arguments.

coef

Estimates.

vcov

Sampling variance-covariance matrix.

jacobian

Jacobian matrix.

fun

Function used ("DeltaGeneric").

See also

Other Delta Method Functions: Delta()

Author

Ivan Jacob Agaloos Pesigan

Examples

object <- glm(
  formula = vs ~ wt + disp,
  family = "binomial",
  data = mtcars
)
def <- list("exp(wt)", "exp(disp)")
DeltaGeneric(
  object = object,
  def = def,
  alpha = 0.05
)
#> Call:
#> DeltaGeneric(object = object, def = def, alpha = 0.05)
#>              est     se       z      p    2.5%   97.5%
#> exp(wt)   5.0853 7.5805  0.6708 0.5023 -9.7723 19.9429
#> exp(disp) 0.9662 0.0148 65.0838 0.0000  0.9371  0.9952