set the small sample correction factor applied in `boottest()`

## Arguments

- adj
Logical scalar, defaults to TRUE. If TRUE, applies a small sample correction of (N-1) / (N-k) where N is the number of observations and k is the number of estimated coefficients excluding any fixed effects projected out in either fixest::feols() or lfe::felm().

- fixef.K
Character scalar, equal to 'none': the fixed effects parameters are discarded when calculating k in (N-1) / (N-k).

- cluster.adj
Logical scalar, defaults to TRUE. If TRUE, a cluster correction G/(G-1) is performed, with G the number of clusters.

- cluster.df
Either "conventional"(the default) or "min". Controls how "G" is computed for multiway clustering if cluster.adj = TRUE. Note that the covariance matrix in the multiway clustering case is of the form V = V_1 + V_2 - V_12. If "conventional", then each summand G_i is multiplied with a small sample adjustment G_i / (G_i - 1). If "min", all summands are multiplied with the same value, min(G) / (min(G) - 1)

## Examples

```
boot_ssc(adj = TRUE, cluster.adj = TRUE)
#> $adj
#> [1] TRUE
#>
#> $fixef.K
#> [1] "none"
#>
#> $cluster.adj
#> [1] TRUE
#>
#> $cluster.df
#> [1] "conventional"
#>
#> attr(,"class")
#> [1] "boot_ssc.type"
boot_ssc(adj = TRUE, cluster.adj = TRUE, cluster.df = "min")
#> $adj
#> [1] TRUE
#>
#> $fixef.K
#> [1] "none"
#>
#> $cluster.adj
#> [1] TRUE
#>
#> $cluster.df
#> [1] "min"
#>
#> attr(,"class")
#> [1] "boot_ssc.type"
```