coef.ivreg {ivreg}

Methods for "ivreg" Objects

Description

Various methods for processing "ivreg" objects; for diagnostic methods, see ivregDiagnostics.

Usage

## S3 method for class 'ivreg'
coef(object, component = c("stage2", "stage1"), complete = TRUE, ...)

## S3 method for class 'ivreg'
vcov(object, component = c("stage2", "stage1"), complete = TRUE, ...)

## S3 method for class 'ivreg'
confint(
  object,
  parm,
  level = 0.95,
  component = c("stage2", "stage1"),
  complete = TRUE,
  vcov. = NULL,
  df = NULL,
  ...
)

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

## S3 method for class 'ivreg'
estfun(x, ...)

## S3 method for class 'ivreg'
vcovHC(x, ...)

## S3 method for class 'ivreg'
terms(x, component = c("regressors", "instruments", "full"), ...)

## S3 method for class 'ivreg'
model.matrix(
  object,
  component = c("regressors", "projected", "instruments"),
  ...
)

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

## S3 method for class 'ivreg'
predict(
  object,
  newdata,
  type = c("response", "terms"),
  na.action = na.pass,
  se.fit = FALSE,
  interval = c("none", "confidence", "prediction"),
  df = Inf,
  level = 0.95,
  weights,
  ...
)

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

## S3 method for class 'ivreg'
summary(object, vcov. = NULL, df = NULL, diagnostics = NULL, ...)

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

## S3 method for class 'ivreg'
anova(object, object2, test = "F", vcov. = NULL, ...)

## S3 method for class 'ivreg'
update(object, formula., ..., evaluate = TRUE)

## S3 method for class 'ivreg'
residuals(
  object,
  type = c("response", "projected", "regressors", "working", "deviance", "pearson",
    "partial", "stage1"),
  ...
)

## S3 method for class 'ivreg'
Effect(focal.predictors, mod, ...)

## S3 method for class 'ivreg'
formula(x, component = c("complete", "regressors", "instruments"), ...)

## S3 method for class 'ivreg'
find_formula(x, ...)

## S3 method for class 'ivreg'
Anova(mod, test.statistic = c("F", "Chisq"), ...)

## S3 method for class 'ivreg'
linearHypothesis(
  model,
  hypothesis.matrix,
  rhs = NULL,
  test = c("F", "Chisq"),
  ...
)

## S3 method for class 'ivreg'
alias(object, ...)

## S3 method for class 'ivreg'
qr(x, ...)

## S3 method for class 'ivreg'
weights(object, type = c("variance", "robustness"), ...)

Arguments

object, object2, model, mod

An object of class "ivreg".

component

For terms, "regressors", "instruments", or "full"; for model.matrix, "projected", "regressors", or "instruments"; for formula, "regressors", "instruments", or "complete"; for coef and vcov, "stage2" or "stage1".

complete

If TRUE, the default, the returned coefficient vector (for coef()) or coefficient-covariance matrix (for vcov) includes elements for aliased regressors.

...

arguments to pass down.

parm

parameters for which confidence intervals are to be computed; a vector or numbers or names; the default is all parameters.

level

for confidence or prediction intervals, default 0.95.

vcov.

Optional coefficient covariance matrix, or a function to compute the covariance matrix, to use in computing the model summary.

df

For summary, optional residual degrees of freedom to use in computing model summary. For predict, degrees of freedom for computing t-distribution confidence- or prediction-interval limits; the default, Inf, is equivalent to using the normal distribution; if NULL, df is taken from the residual degrees of freedom for the model.

x

An object of class "ivreg" or "summary.ivreg".

newdata

Values of predictors for which to obtain predicted values; if missing predicted (i.e., fitted) values are computed for the data to which the model was fit.

type

For predict, one of "response" (the default) or "terms"; for residuals, one of "response" (the default), "projected", "regressors", "working", "deviance", "pearson", or "partial"; type = "working" and "response" are equivalent, as are type = "deviance" and "pearson"; for weights, "variance" (the default) for invariance-variance weights (which is NULL for an unweighted fit) or "robustness" for robustness weights (available for M or MM estimation).

na.action

na method to apply to predictor values for predictions; default is na.pass.

se.fit

Compute standard errors of predicted values (default FALSE).

interval

Type of interval to compute for predicted values: "none" (the default), "confidence" for confidence intervals for the expected response, or "prediction" for prediction intervals for future observations.

weights

Either a numeric vector or a one-sided formula to provide weights for prediction intervals when the fit is weighted. If weights and newdata are missing, the weights are those used for fitting the model.

digits

For printing.

diagnostics

Report 2SLS "diagnostic" tests in model summary (default is TRUE). These tests are not to be confused with the regression diagnostics provided elsewhere in the ivreg package: see ivregDiagnostics.

signif.stars

Show "significance stars" in summary output.

test, test.statistic

Test statistics for ANOVA table computed by anova(), Anova(), or linearHypothesis(). Only test = "F" is supported by anova(); this is also the default for Anova() and linearHypothesis(), which also allow test = "Chisq" for asymptotic tests.

formula.

To update model.

evaluate

If TRUE, the default, the updated model is evaluated; if FALSE the updated call is returned.

focal.predictors

Focal predictors for effect plot, see Effect.

hypothesis.matrix, rhs

For formulating a linear hypothesis; see the documentation for linearHypothesis for details.

See Also

ivreg, ivreg.fit, ivregDiagnostics