Low-level implementations of ei_ridge() and ei_riesz()

No checks are performed on the inputs. Use of ei_ridge() and ei_riesz() is strongly recommended unless many regressions must be fit, e.g., within a tight loop. Only works for a single outcome, i.e., y must be a vector, not a matrix.

Usage

ei_ridge_impl(
  x,
  y,
  z,
  weights = rep(1, nrow(x)),
  bounds = c(-Inf, Inf),
  penalty = NULL,
  vcov = TRUE
)

ei_riesz_impl(x, z, total, weights = rep(1, nrow(x)), penalty)

Arguments

x

A matrix of predictors

y

A vector of outcomes

z

A matrix of covariates

weights

A vector of estimation weights

bounds

A vector c(min, max) of bounds for the outcome.

penalty

The ridge penalty (a non-negative scalar), which must be specified for ei_riesz_impl() but can be automatically estimated with ei_ridge_impl() by providing penalty=NULL.

vcov

If TRUE, calculate and return the covariance matrix of the estimated coefficients. Ignored when bounds are provided.

total

A vector of total observations per unit.

Value

A list with model components.