- Bugfix for tests failing with
`noLongDouble`

- Fixed bugs in
`IRLS`

fitting when providing`weights`

argument when calling`estimatePopsize`

- The
`weightsAsCounts`

option in`controlModel`

now works properly,`dfbeta`

and`dfpopsize`

decrease weight of selected row in a model matrix instead of deleting it when this is set to`TRUE`

`simulate`

method now works for both family object (like`ztpoisson()`

) and for objects returned by`estimatePopsize`

- Introduced
`singleRStaticCountData`

sub class for`singleRclass`

and made`estimatePopsize`

a method so that a new package`singleRcaptureExtra`

(under development) can make all necessary calculations for pop size estimation when providing object fitted by`countreg::zerotrunc`

or`VGAM::vglm`

/`VGAM::vgam`

- Some bugfixes for multicore bootstrap
- Code was re-factored to make further development/maintenance for the package much easier
- Update will be uploaded to
`CRAN`

`semiparametric`

bootstrap now has a much faster sampling algorithm (that does the same job)

Unit tests: * Reduced computational burden of unit tests * Multicore
tests will only be performed after
`TEST_SINGLERCAPTURE_MULTICORE_DEVELOPER`

is set to
`"true"`

via `Sys.setenv`

and
`_R_CHECK_LIMIT_CORES_`

to `false`

- Added
`offset`

argument to`estimatePopsize`

- Added options for parallel computing in
`bootstrap`

and in`dfbeta`

- Added deviance for all negative binomial based models. (NOTE: They are very slow for now and I believe it may change after I verify one theoretical results that will lead to significant speed increase for these computations)
- Overhaul of starting points (new methods and added linear predictors
start in
`IRLS`

) - Code for weights in
`IRLS`

fitting was speed up - Minor bugfixes

- features and improvements:
- Added final
`Hurdleztnegbin`

model - Vastly improved
`redoPopSize`

which now handles bootstrap on a fitted model non standard covariance matrixes`newdata`

argument user supplied`coef`

etc. - Added
`predict.singleR`

method which offers standard error for both`link`

,`response`

as well as`mean`

predictions - No unexpected warnings should occur now in main function when using the package correctly
- All control arguments are now verified before being passed
- Fitting is now more reliable
- Added information about
`stats::optim`

error codes - Added warnings for functions computing deviance

- Added final
- bugfixes:
- fixed bugs occurring when using mathematical functions as part of
formulas i.e. when setting formula to something like:
`y ~ log(x) + I(x ^ t) + I(t ^ 2)`

- fixed bugs occurring when using mathematical functions as part of
formulas i.e. when setting formula to something like:

- features
- Added
`ztoinegbin`

,`oiztnegbin`

and`ztHurdlenegbin`

models - Added an optional arguments to all family-functions to specify a link function for distribution parameters
- Updated and standardized documentation
- Added more warnings
- Added some more methods for
`singleR`

class in some commonly used`glm`

functions, in particular`texreg::screenreg`

should work well now

- Added
- changes
- Changed some default arguments
- Added option to save logs from
`IRLS`

fitting

- bugfixes
- Fixed some issues with intercept only models
- Fixed some slight miscalculations in information matrixes for one inflated models making fitting them much more reliable

- github repository
- More and better
`Rcmd`

tests

- More and better

- features:
- Added function that implements population size estimates for stratas
- More warnings in fitting
- More options in control functions
- Corrected/implemented deviance residuals for more models

- changes:
- Now the whole package uses
`cammelCase`

- Performance upgrades
- Corrected some miss calculated moments
- Change exported data so that factors are actually factors not just characters
- Removed unused dependency

- Now the whole package uses
- github repository
- Added automated
`R-cmd`

check

- Added automated

- features:
- Basically all of documentation was redone and now features most of important theory on SSCR methods and some information on (v)glms
- Added checks on positivity of working weights matrixes to stabilise
`"IRLS"`

algorithm - Added most of sandwich capabilities to the package, in particular:
- S3 method for
`vcovHC`

was implemented `vcovCL`

should work on`singleR`

class objects should work with`"HC0"`

and`"HC1"`

`type`

argument values

- S3 method for
- Basic version of function
`redoPopEstimation`

for updating the population size estimation after post-hoc procedures was implemented `popSizeEst`

function for extracting population size estimation results was implemented- Minor improvements to memory usage were made and computation was speed up a little
- Changed names of mle and robust fitting methods to optim and IRLS respectively
- Some bugfixes
- More warnings messages in
`estimate_popsize.fit`

- features:
- Multiple new models
`IRLS`

generalised for distributions with multiple parameters- bugfixes
- QOL improvements
- extended bootstrap and most other methods for new models

- features:
- control parameters for model
- control parameters for regression in bootstrap sampling
- leave one out diagnostics for popsize and regression parameters
(
`dfbetas`

were corrected) - fixes for Goodness of fit tests in zero one truncated models
- computational improvements in
`IRLS`

- other small bugfixes

- bug fixes and some of the promised features for 0.2.0 in particular
- More tiny tests
- Some fixes for marginal frequencies
- Deviance implemented
- dfbetas and levarage matrix
- Parametric bootstraps work correctly for the most part there is just some polishing left to do

- first version of the package released