NEWS.md

maars 1.2.0

• Write vignette on effect of increasing B in (n-out-of-n) empirical / multiplier / subsampling bootstrap samples on coverage when compared to sandwich

maars 1.1.0

• Change Significance heading in our summary output to be abbreviated to Signif: to be consistent with lm() output
• Change column ordering for bootstrap standard errors and t-statistics rigorously
• Change p-value format to be 2/3 digits
• Clean R/scripts_and_filters/experiments/ dir, remove old experiments
• Clean up script that gets metadata of maars function metadata from pkgdown
• Remove all base:: prefix use e.g. base::return()
• Change dplyr::summarise to dplyr::summarize for spelling consistency
• Ensure all stats functions use the stats:: prefix
• Fix .data related rlang issues
• We shouldn't name a variable df since this conflicts with stats::df. We should change this after the demo
• Clean vignette. Leave the plot in the vignette (to be moved elsewhere)
• Updated the corrected Boston Housing Dataset with citations. Add unit tests for the corrections
• Clean up spelling notes
• Change multiplier weights code to use switch based approach
• Switch to model.matrix in sandwich variance and use residuals in the computation
• Update maars to have a package level doc. Add @importFrom statements
• Fix NOTE by adding .gitkeep in vignettes to .RBuildignore
• Fix NOTE by DESCRIPTION meta-information by making it a couple of sentences. This is a placeholder and we should refine it before official CRAN release.
• Consolidate boston-housing.R and la-county.R files into a single data-maars.R files. Consolidate test files accordingly
• Make some minor changes to the vignette
• Add styling to our code using the Makefile and styler::style_dir(here::here('R')) and for tests
• Have a make style which does both R and tests
• Make sure styling does not include vignettes
• Ensure that url_check() are all resolved for CRAN
• Remove DOI entries from inst/REFERENCES.bib since they can cause CRAN url issues
• Add search functionality to pkgdown our site.
• Use MIT License
• Fix the no visible binding for global variable errors in our code
• Remove mixture of %>% and base code, and just break pipes into variables
• Change all attr(obj, "class") <- c("obj_class_name") to be of the form class(obj) <- "obj_class_name" for consistency
• Change dplyr::_all scoped words using the superseded across function

maars 1.0.0

• Set the default digits = 3 formatting in summary.maars_lm printed output
• Move summary.maars_lm, print.maars_lm, plot.maars_lm methods into maars-lm.R file
• Merge lm-var.R code into into sandwich-var.R since they are both default estimators
• Use the la_county tibble directly from maars in our vignette
• Re-write vignette to produce Table 1 from Buja et. al. 1 to include new get_summary() function
• Write get_plot(), get_summary(), summary.maars_lm(), and get_confint(), confint.maars_lm() functionality for maars_lm() objects
• Change the statistic based on the F-distribution to one based on the Chi-square
• Write plots function with default options and wrap around get_plot()
• Add more Cook's distance plots similar to lm() output
• Add confidence interval plots to the maars_lm plot output
• Print assumptions i.e. for all run maars standard errors. So sand, well_specified assumptions are printed by default, and other standard errors
• Add assumption string for comp_lm_var using glue::glue() and improve formatting
• Amend get_confint() to return tidy tibble output
• Just show term, conf.low, conf.high for confint(maars_lm). Fix it to be the same as confint(lm)
• Add la_county tibble to our package
• Change README.Rmd to use devtools rather than remotes as the preferred package installation
• Add devtools to Suggests in DESCRIPTION so that vignettes use our latest code
• Ensure that the la_county tibble is documented method
• Write residual bootstrap assumptions to be the same as the well specified lm() model
• Include weights type in assumptions for multiplier bootstrap
• Include n in assumptions for empirical bootstrap

maars 0.7.0

• Write function to create maars_lm object from comp_var
• write a as.maars_lm function to be run on an lm object
• write confint.maars_lm method
• write print.maars_lm method
• Write summary.maars_lm method
• Write plot.maars_lm, currently for lm objects
• Correct typo in maars release 0.6.0 in NEWS.md
• Use GPL-2 and GPL-3 LICENCE
• Remove the MIT LICENCE files
• We would like to thank Alex Reinhart for his kind assistance in various aspects of this release

maars 0.6.0

• update the documentation of comp_var and of the estimators of the variance
• Adapt tests to handle the new function comp_var
• create a function to nicely return a string containing the assumptions behind each computation of the variance (e.g., call it get_assumptions)
• compute covariance matrix V of coefficients estimates for the bootstrap
• Make weights_type for comp_boot_mul to be default rademacher
• Handle assertions for multiplier bootstrap
• rewrite comp_var to handle the list outputs generated by the estimators of the variance
• adapt tests to handle the list outputs generated by the variance estimators
• change the bootstrap functions such that they return a list and compute get_summary within the function
• make the names of the lists generated by the estimators of the variance consistent
• rewrite the sandwich function to return a list
• write documentation for get_summary
• Check that we define/design inputs consistently for comp_var
• Ensure that default values for all inputs is set to NULL for empirical bootstrap, multiplier bootstrap, residual bootstrap
• Perform input assertion checking for all inputs consistently for comp_var
• Create an if-then-else skeleton for comp_var
• Add residual bootstrap to comp_var
• Update tests for comp_var for empirical bootstrap, multiplier bootstrap, residual bootstrap

maars 0.5.0

• Rename function names to be more consistent e.g. remove qr from empirical bootstrap names
• Ensure renamed function names are also correctly changed in the corresponding test files
• Split our pkgdown references into suitable categories like usethis, here is an example
• Change specific functions to be private by removing #' @export in roxygen2 and replacing it with #' @keywords internal

maars 0.4.0

• Include .gitattributes file
• We need to set.seed in all our vignette chunks. This is for reproducibility, but to also avoid merge conflicts every time we rebuild the package using make build_package
• roxygen2: Rewrite documentation of the functions making the style more consistent across functions. For example, we could adopt the style used for the quantile function
• roxygen2: insert dots at end of sentences in roxygen2. See below
• roxygen2: use @details responsibly. See below
• roxygen2: replace var_name with \code{var_name}. See below
• ggplot2: Replace hardcoded values 1.96 with appropriate outputs from statistics functions, in vignettes
• Check the order in which we have our functions written in each file
• ggplot2: We should break up our ggplot2 code into separate plots and then combine them using +. This will make it much easier to manage the code and make it readable
• ggplot2: Need to be consistent with our ggplot2 themes used in our plots. See ggplot2 theme wrapper below
• ggplot2: Need to be consistent with the ggplot2 font and other settings used in our plots. As a preference we should only use labs for example. See ggplot2 theme wrapper below
• ggplot2: Add names_prefix = "q" to pivot_wider for the ggplot2 code i.e. to avoid .data$0.275 issue. Note the "q" here stands for quantile.
• Create a utils-common.R similar to the selectiveInference package, ensure that common functions are put in this file
• clean up the tests directory i.e. delete unused R test files
• clean up the R directory i.e. delete unused R files
• We should add #' @importFrom rlang .data in all our functions under #' @export
• Fix R CMD CHECK error caused in vignette, namely this one
• Add stringr to DESCRIPTION
• Change multiplier bootstrap weights to be applied inside purrr e.g using purrr::map2 rather than generating the e matrix up front. Conduct benchmarks of this to test speed, so that current version still has it's place in benchmarking
• For vignette should knitr::kable package instead of DT package and just need to ensure Table 1 is correctly populated
• For vignette we just need to ensure Table 1 is correctly formatted i.e. use LaTeX for headings, consistent width, and captions. See here for the use of LaTeX in knitr::kable heading rows
• Add Rmd line wrap hooks similar to Yihui Xie's approach and the oxforddown approach
• Add doc for weight_type in multiplier bootstrap
• Remove default value of B in multiplier variance
• Allow for 5 types of weights for multiplier bootstrap i.e. std_gaussian, rademacher, and mammen, webb, gamma
• Update credits in Licence and License.md

maars 0.3.0

• Implement an efficient multiplier bootstrap for lm standard errors
• Implement the empirical bootstrap for lm standard errors
• Implement the empirical bootstrap for glm standard errors
• Change the input lm_fit to be mod_object in all of our functions
• Check that we have referenced functions using stats::, dplyr::, etc
• Add the t-test values in Table 1 of the Models As Approximations - Part 1 paper
• Add input validation for our bootstrap and variance estimation functions e.g. B must be a positive integer
• Set a seed for the unit tests
• Update Readme.Rmd to add installation instructions and link to official package

maars 0.2.0

• Create the comp_sandwich_qr_var function with documentation, tests, benchmarking

maars 0.1.0

maars 0.0.0.9000

• Added a NEWS.md file to track changes to the package.