cruv4: RUV4's second step.
In dcgerard/vicar: Various Ideas for Confounder Adjustment in Regression

This is the old version that only works for one covariate of interest. Use cruv4_multicov for the more recent version.

cruv4(
  betahat_ols,
  alpha_scaled,
  sig_diag_scaled,
  ctl,
  degrees_freedom,
  gls = TRUE,
  likelihood = "t"
)

`betahat_ols`	A matrix of numerics with one column. The ols estimates of beta.
`alpha_scaled`	A matrix of numerics. The estimated coefficients of the unobserved confounders.
`sig_diag_scaled`	A vector of positive numerics. The estimated standard errors of `betahat_ols`.
`ctl`	A vector of logicals of length `ncol(Y)`. If position i is `TRUE` then position i is considered a negative control.
`degrees_freedom`	A positive numeric. The degrees of freedom of the t-likelihood if using it.
`gls`	A logical. Should we use generalized least squares (`TRUE`) or ordinary least squares (`FALSE`) for estimating the confounders? The OLS version is equivalent to using RUV4 to estimate the confounders.
`likelihood`	Either `"normal"` or `"t"`. If `likelihood = "t"`, then the user may provide the degrees of freedom via `degrees_freedom`.