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).

Log message:
(math/R-sandwich) Updated 3.0.1 to 3.0.2

# sandwich 3.0-2

* Added new argument `aggregate = TRUE` to `meatPL()` which is thus inherited by
  `vcovPL()`. By default, this still yields the Driscoll & Kraay (1998) \ 
covariance
  matrix. When setting `aggregate = FALSE` the cross-sectional and cross-serial
  correlation is set to zero, yielding the "pure" panel Newey-West \ 
covariance
  matrix.

* Bug fix in `vcovCL(..., type = "HC2")` for `glm` objects or `lm` objects
  with weights. The code had erroneously assumed that the hat matrices were
  all symmetric (as in the `lm` case without weights). This is corrected now.
  (Detected and reported by Bixi Zhang.)

* Issue a warning in `vcovHC()` for HC2/HC3/HC4/HC4m/HC5 if any of the hat values
  are numerically equal to 1. This leads to numerically unstable covariances,
  in the most extreme case `NaN` because the associated residuals are equal to
  0 and divided by 0. (Suggested by Ding Peng and John Fox.)

* Speed improvement in `vcovBS.lm()`: For `"xy"` bootstrap, \ 
`.lm.fit()` rather than
  `lm.fit()` is used which is somewhat more efficient in some situations (suggested
  by Grant McDermott). For `"residual"` and wild bootstrap, the \ 
bootstrap by default
  still samples coefficients via QR decomposition in each iteration (`qrjoint = \ 
FALSE`)
  but may alternatively sample the dependent variable and then apply the QR
  decomposition jointly only once (`qrjoint = TRUE`). If the sample size (and the
  number of coefficients) is large, then `qrjoint = TRUE` may be significantly faster
  while requiring much more memory (proposed by Alexander Fischer).

* Enable passing score matrix (as computed by `estfun()`) directly to
  `bwAndrews()` and `bwNeweyWest()`. If this is used, the score matrix should
  either have a column `(Intercept)` or the `weights` argument should be set
  appropriately to identify the column pertaining to the intercept (if any).

* The vignettes have been tweaked so that they still "run" without \ 
technical errors
  when suggested packages (listed in the VignetteDepends) are not available. This is
  achieved by defining replacement functions that do not fail but lead to partially
  non-sensical output. A warning is added in the vignettes if any of the replacements
  is used.

Log message:
math: Replace RMD160 checksums with BLAKE2s checksums

All checksums have been double-checked against existing RMD160 and
SHA512 hashes

Log message:
math: Remove SHA1 hashes for distfiles

Log message:
(math/R-sandwich) Updated 2.5.1 to 3.0.1

# sandwich 3.0-1

* Extended the "Getting started" page with information on how to use \ 
_sandwich_ in
  combination with the _modelsummary_ package (Arel-Bundock) based on _broom_
  infrastructure (Robinson, Hayes, Couch). (Based on ideas from Grant McDermott.)
  <https://sandwich.R-Forge.R-project.org/articles/sandwich.html>

* Catch `NA` observations in `cluster` and/or `order.by` indexes for `vcovCL()`,
  `vcovBS()`, `vcovPL()`, and `vcovPC()`. Such missing observations cannot be
  handled in the covariance extractor functions but need to be addressed prior
  to fitting the model object, either by omitting these observations or by
  imputing the missing values. (Raised by Alexander Fischer on StackOverflow
  \ 
<https://stackoverflow.com/questions/64849935/clustered-standard-errors-and-missing-values>.)

* In `vcovHC()` if there are `estfun()` rows that are all zero and `type = \ 
"const"`,
  then the working residuals for `lm` and `glm` objects are obtained via
  `residuals()` rather than `estfun()`. (Prompted by an issue raised by
  Alex Torgovitsky.)

# sandwich 3.0-0

* Release of version 3.0-0 accompanying the publication of the paper
  "Various Versatile Variances: An Object-Oriented Implementation of
  Clustered Covariances in R." together with Susanne Koell and Nathaniel Graham
  in the _Journal of Statistcal Software_ at \ 
<https://doi.org/10.18637/jss.v095.i01>.
  The paper is also provided as a vignette in the package as
  `vignette("sandwich-CL", package = "sandwich")`.

* Improved or clarified notation in Equations 6, 9, 21, and 22 (based on
  feedback from Bettina Gruen).

* The documentation of the HC1 bias correction for clustered covariances
  in `vignette("sandwich-CL", package = "sandwich")` has \ 
been corrected (Equation 15).
  While both the code in `vcovCL()` and the corresponding documentation `?vcovCL`
  always correctly used (n-1)/(n-k), the vignette had incorrectly stated it as
  n/(n-k). (Reported by Yves Croissant.)

* The package is also accompanied by a `pkgdown` website on R-Forge now:
  <https://sandwich.R-Forge.R-project.org/>
  This essentially uses the previous content of the package (documentation,
  vignettes, NEWS) and just formatting was enhanced. But a few new features
  were also added:

  - A "Get started" vignette for the `pkgdown` page (but not shipped in the
    package) providing an introduction to the package and listing all
    variance-covariance functions provided with links to further details.
  - R/Markdown overview vignettes for the `pkgdown` page (but also not shipped
    in the package) linking the `Sweave`-based PDF vignettes so that they are
    easily accessible online.
  - A `README` with very brief overview for the `pkgdown` title page.
  - A nice logo, kindly provided by Reto Stauffer.

* All kernel weights functions in `kweights()` are made symmetric around zero now
  (suggested by Christoph Hanck). The quadratic spectral kernal is approximated
  by `exp(-c * x^2)` rather than `1` for very small `x`.

* In case the `Formula` namespace is loaded, warnings are suppressed now for
  processing formula specifications like `cluster = ~ id` in `expand.model.frame()`.
  Otherwise warnings may occur with the `|` separator in multi-part formulas with
  factors. (Reported by David Hugh-Jones.)

* The `bread()` method for `mlm` objects has been improved to also handle
  _weighted_ `mlm` objects. (Suggested by James Pustejovsky.)

Log message:
Update all R packages to canonical form.

The canonical form [1] of an R package Makefile includes the
following:

- The first stanza includes R_PKGNAME, R_PKGVER, PKGREVISION (as
  needed), and CATEGORIES.

- HOMEPAGE is not present but defined in math/R/Makefile.extension to
  refer to the CRAN web page describing the package.  Other relevant
  web pages are often linked from there via the URL field.

This updates all current R packages to this form, which will make
regular updates _much_ easier, especially using pkgtools/R2pkg.

[1] http://mail-index.netbsd.org/tech-pkg/2019/08/02/msg021711.html