diag_fit_reg_rwgt: Obtain estimates of GLM or OLS under reweighting of one or...
In shamindras/maars: Tidy Inference Under Misspecified Statistical Models in R

Description Usage Arguments Details Value Examples

diag_fit_reg_rwgt returns estimates for GLM and OLS under reweighting of multiple regressors. The function estimates a set of coefficients for several configurations of the reweighting of the reweighting of each regressor.

diag_fit_reg_rwgt(
  mod_fit,
  terms_to_rwgt,
  B = 100,
  m = NULL,
  grid_centers = NULL,
  grid_method = "quantiles",
  n_grid = 9
)

`mod_fit`	An object of class `lm` or `glm` to fit on the data. This object should contain the formula, the data, and, in case of `glm`, the family.
`terms_to_rwgt`	A vector of characters corresponding to the names of the regressors to be reweighted.
`B`	An integer corresponding to the number of bootstrap repetitions or number of bootstrap samples to be drawn. Default is set to `100`.
`m`	An integer corresponding to the number of observations to be sampled with replacement from the data set in each bootstrap repetition. Default is set to the size of the data set.
`grid_centers`	A data frame containing the names of the regressors as columns and the corresponding reweighting centers. Each column corresponds to a different regressor, whose name is specified in the name of the column. Default is set to `NULL`.
`grid_method`	A character which specifies the method used to construct the grid of reweighting centers. The grid can consist either of evenly spaced values between the maximum and the minimum (`grid_method='regular'`) or based on the quantiles between the first and the ninth deciles (`grid_method='quantiles'`). Default is set to `'quantile'`.
`n_grid`	An integer corresponding to the number of reweighting centers for the grid. Default is set to `9`.

The model extracted from mod_fit is fitted on B data sets sampled via m-out-of-n empirical bootstrap using weighted regression where the predictors to be reweighted are specified in terms_to_rwgt and have reweighting centers given by grid_centers. Using the default parameters, the function will compute the estimates for a grid based on the second to first to the ninth deciles of each regressor.

A tibble containing the number of the bootstrapped data set (b), the size of each bootstrapped data set (m), the value of the reweighting centers (term_rwgt_center) and the name of the regressor under reweighting (term_rwgt), and the estimates of the regression coefficients (term and estimate).

## Not run: 
set.seed(1321312)
# Get OLS estimates under reweighting of all regressors with default grid
n <- 1e3
X1 <- stats::rnorm(n, 0, 1)
X2 <- stats::rnorm(n, 0, 3)
y <- 2 + X1 + X2 * 0.3 + stats::rnorm(n, 0, 1)
reg_df <- tibble::tibble(y = y, X1 = X1, X2 = X2, n_obs = 1:length(X1))
mod_fit <- stats::lm(y ~ X1 + X2, reg_df)
ols_rwgt <- diag_fit_reg_rwgt(mod_fit, c("X1", "X2"))

# Display the output
print(ols_rwgt)

# Get OLS estimates under reweighting of all regressors by feeding grid of centers into the function
ols_rwgt_grid_fixed <- diag_fit_reg_rwgt(mod_fit, "X1", grid_centers = data.frame(X1 = c(0, 1)))

#' # Display the output
print(ols_rwgt_grid_fixed)

## End(Not run)