Log Message:
(math/R-sandwich) Updated 3.0.2 to 3.1.1

# sandwich 3.1-1

* In `meatPL()` the case of cross-section data (i.e., all elements of `order.by`
  being equal) is handled consistently even if `aggregate = TRUE` (reported by
  Christof Schoetz).

* Fix `bread()` method for `survreg()` objects in case the latter already used a
  "robust" sandwich variance. In that case `$naive.var` rather than \ 
`$var` has
  to be used for the bread (reported by Daniel Klinenberg).

* Improve warnings in `vcovHC()` for hat values numerically equal to 1. (Suggested by
  Sanford Weisberg and John Fox.)

# sandwich 3.1-0

* Added jackknife estimator in all `vcovBS()` methods (suggested by Joe Ritter).
  This is of particular practical interest in linear regression models where the
  (clustered) jackknife and the (clustered) HC3 (or CV3, without cluster adjustment)
  estimator coincide. In nonlinear models (including non-Gaussian GLMs) the \ 
jackknife and
  the HC3 estimator do not coincide but the jackknife might still be a useful
  alternative when the HC3 cannot be computed.

* Added a new convenience interface `vcovJK()` for the jackknife covariance whose
  default method simply calls `vcovBS(..., type = "jackknife")` (also \ 
suggested by
  Joe Ritter, for more details see the previous item).

* Added fractional-random-weight bootstrap, also known as Bayesian bootstrap, in all
  `vcovBS()` methods (suggested by Noah Greifer and Grant McDermott). This is an
  alternative to the classical xy bootstrap which has the computational advantage
  that all observations are always part of the bootstrap samples with positive
  weights drawn from a Dirichlet distribution. As weights can become close to zero
  but no observations are excluded completely, this can stabilize the computation of
  models that are not well-defined on all subsets.

* Support weights, offsets, and different fitting methods in `lm` and `glm` objects
  in the respective `vcovBS()` methods (reported by Noah Greifer).

* More verbose error messages in `bwAndrews()` and `bwNeweyWest()` when bandwidth
  cannot be computed, e.g., due to singular regressor variables (suggested by
  Andrei V. Kostyrka).

* Fix `bread()` method for `coxph()` objects in case the latter already used a
  "robust" sandwich variance. In that case `$naive.var` rather than \ 
`$var` has
  to be used for the bread (reported by Alec Todd).

* Fix `plm::plm(..., index = ...)` calls which incorrectly used `indexes = ...`
  (as in `plm.data()`, reported by Kevin Tappe).