v0.6.0: Making glmmTMB conditional + removing deprecated (#8)

* removing `call. = FALSE`

- originally inspired by
https://adv-r.hadley.nz/conditions.html?q=call.%20=%20FALSE#errors-1 but
I think it's not as helpful now

* removing deprecated functions

- it's time now.

* document updates:

- removed (previously deprecated) functions no longer in exported
- docs updated (with roxygen update)

* need glmmTMB for the last few tests

* adding future.seed = TRUE to solve RNG from future.apply

* increasing minimum version of glmmTMB

* update the readme

- run glmmTMB-dependent blocks conditionally
- minor cleanup

* adding conditional eval to vignette

* adding clarification about non-parametric bootstrap

* increasing version to 0.6.0

* adding cran-comments and news updates

* spelling error

* adding test envs to cran comments

Author: Colman Humphrey

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: glmmboot
 Type: Package
 Title: Bootstrap Resampling for Mixed Effects and Plain Models
-Version: 0.5.1
+Version: 0.6.0
 Authors@R: person("Colman", "Humphrey", email = "humphrc@tcd.ie",
   role = c("aut", "cre"))
 Description: Performs bootstrap resampling for most models that update() works for. There
@@ -19,12 +19,12 @@ Depends:
 Imports: methods,
     stats
 Suggests:
-    glmmTMB (>= 0.2.1),
+    glmmTMB (>= 1.1.0),
     testthat (>= 0.11.0),
     parallel (>= 3.0.0),
     future.apply (>= 1.1.0),
     knitr,
     rmarkdown,
     covr
-RoxygenNote: 7.0.2
+RoxygenNote: 7.1.1
 VignetteBuilder: knitr

NAMESPACE

@@ -1,8 +1,5 @@
 # Generated by roxygen2: do not edit by hand
 
-export(BootCI)
-export(BootGlmm)
-export(CombineResampledLists)
 export(bootstrap_ci)
 export(bootstrap_model)
 export(combine_resampled_lists)

NEWS.md

@@ -1,3 +1,13 @@
+# glmmboot 0.6.0
+
+* Removing previously deprecated functions (deprecated as of 0.4.0)
+* Adding conditional evaluation for tests and the vignette (and the readme)
+  for `glmmTMB`, in case it's not present / installable on a given system (as
+  it's only a suggested package)
+* Removing `call. = FALSE` for errors and warnings
+* adding `future.seed = TRUE` to `future.apply::future_lapply` call for better RNG
+* Minor vignette and README copy edits
+
 # glmmboot 0.5.1
 
 * Changing a `donttest` to a `dontrun` within an example.

R/bootstrap_ci.R

@@ -91,12 +91,12 @@ bootstrap_individual_ci <- function(base_matrix = NULL,
     if (is.null(probs)) {
         if (alpha_level < 0 | alpha_level > 0.5) {
             stop("Can't calculate a two-sided CI with this alpha value, ",
-                 "must be in (0, 0.5)", call. = FALSE)
+                 "must be in (0, 0.5)")
         }
         probs <- sort(c(alpha_level / 2, 1 - alpha_level / 2))
     }
     if (max(probs) > 1 || min(probs) < 0) {
-        stop("Probabilities should be in (0,1)", call. = FALSE)
+        stop("Probabilities should be in (0,1)")
     }
 
     base_row_names <- rownames(base_matrix)
@@ -107,7 +107,7 @@ bootstrap_individual_ci <- function(base_matrix = NULL,
     }))
 
     if (mean(name_match) != 1) {
-        stop("Naming mismatch from base to list of coefs", call. = FALSE)
+        stop("Naming mismatch from base to list of coefs")
     }
 
     resampled_ests_vecs <- lapply(1:nrow(base_matrix), function(j){
@@ -239,24 +239,6 @@ ci_variable <- function(base_est,
 }
 
 
-#' @rdname bootstrap_ci
-#' @export
-#' @param alp_level
-#' now alpha_level
-BootCI <- function(base_coef_se = NULL, # nocov start
-                   resampled_coef_se = NULL,
-                   orig_df = NULL,
-                   alp_level = 0.05,
-                   probs = NULL){
-    .Deprecated("bootstrap_ci")
-    bootstrap_ci(base_coef_se = base_coef_se,
-                 resampled_coef_se = resampled_coef_se,
-                 orig_df = orig_df,
-                 alpha_level = alp_level,
-                 probs = probs)
-} # nocov end
-
-
 #' Combines output from multiple bootstrap_model calls
 #'
 #' If you run glmmboot on e.g. a grid of computers,
@@ -333,12 +315,3 @@ combine_resampled_lists <- function(...,
     bootstrap_ci(base_coef_se = reg_base_coef,
                  resampled_coef_se = reg_resampled)
 }
-
-#' @rdname combine_resampled_lists
-#' @export
-CombineResampledLists <- function(..., # nocov start
-                                  return_combined_list = FALSE){
-    .Deprecated("combine_resampled_lists")
-    combine_resampled_lists(...,
-                            return_combined_list = return_combined_list)
-} # nocov end

R/bootstrap_methods.R

@@ -122,8 +122,7 @@ gen_resampling_index <- function(orig_list,
                                  sampled_list){
     if (length(orig_list) != length(sampled_list)) {
         stop("lists must be the same length ",
-             "(the original variables and the sampled variables)",
-             call. = FALSE)
+             "(the original variables and the sampled variables)")
     }
 
     ## coercing to character means this works for all types

R/bootstrap_model.R

@@ -127,12 +127,12 @@ bootstrap_model <- function(base_model,
         } else {
             stop("base_data cannot be automatically inferred, ",
                  "please supply data as base_data ",
-                 "to this function", call. = FALSE)
+                 "to this function")
         }
 
         warning("Please supply data through the argument base_data; ",
                 "automatic reading from your model can produce ",
-                "unforeseeable bugs.", call. = FALSE)
+                "unforeseeable bugs.")
     }
 
     if (missing(parallelism)) {
@@ -142,7 +142,7 @@ bootstrap_model <- function(base_model,
             if (!requireNamespace("parallel", quietly = TRUE)) { # nocov start
                 stop("setting `num_cores` greater than 1 without setting ",
                      "`parallelism` uses `package:parallel`, ",
-                     "but it's not installed", call. = FALSE)
+                     "but it's not installed")
             }
             parallelism <- "parallel"  # nocov end
         } else {
@@ -152,25 +152,23 @@ bootstrap_model <- function(base_model,
         parallelism <- match.arg(parallelism)
         if (parallelism == "none" && !is.null(num_cores) && num_cores > 1) {
             stop("contradiction between `parallelism = \"none\"` ",
-                 "and `num_cores = ", num_cores, "`; please resolve",
-                 call. = FALSE)
+                 "and `num_cores = ", num_cores, "`; please resolve")
         }
         if (parallelism == "future") {
             if (!requireNamespace("future.apply", quietly = TRUE)) { # nocov start
                 stop("`parallelism = \"future\"` uses `package:future.apply`, ",
-                     "but it's not installed", call. = FALSE)
+                     "but it's not installed")
             } # nocov end
             if (!is.null(num_cores)) {
                 stop("with `parallelism = \"future\"`, the `num_cores` ",
                      "argument is not used to set up the backend; ",
-                     "use `future::plan` instead",
-                     call. = FALSE)
+                     "use `future::plan` instead")
             }
         }
         if (parallelism == "parallel") {
             if (!requireNamespace("parallel", quietly = TRUE)) { # nocov start
                 stop("`parallelism = \"parallel\"` uses `package:parallel`, ",
-                     "but it's not installed", call. = FALSE)
+                     "but it's not installed")
             } # nocov end
 
             if (is.null(num_cores)) { # nocov start
@@ -183,7 +181,7 @@ bootstrap_model <- function(base_model,
 
     if (parallelism != "future" && !is.null(future_packages)) {
         stop("Argument `future_packages` should only be set when ",
-             "using `parallelism = \"future\"`", call. = FALSE)
+             "using `parallelism = \"future\"`")
     }
 
     ##------------------------------------
@@ -205,7 +203,7 @@ bootstrap_model <- function(base_model,
     } else {
         if (!list_of_matrices(base_coef)) {
             stop("currently this method needs `coef(summary(base_model))` ", # nocov start
-                 "to be a matrix, or a list of them", call. = FALSE) # nocov end
+                 "to be a matrix, or a list of them") # nocov end
         }
         ## only calc not_null once, but local scope the result
         extract_coef <- (function(not_null){
@@ -234,7 +232,7 @@ bootstrap_model <- function(base_model,
         if (sum(rand_cols %in% resample_specific_blocks) == 0 &&
             length(rand_cols) > 0) {
             stop("No random columns from formula found ",
-                 "in resample_specific_blocks", call. = FALSE)
+                 "in resample_specific_blocks")
         }
         rand_cols <- rand_cols[rand_cols %in% resample_specific_blocks]
     }
@@ -338,8 +336,7 @@ bootstrap_model <- function(base_model,
     }
     if (any(error_ind)) {
         stop("could not generate error-free resamples in ", # nocov start
-             max_redos, " attempts",
-             call. = FALSE) # nocov end
+             max_redos, " attempts") # nocov end
     }
 
     if (return_coefs_instead) {
@@ -361,37 +358,6 @@ bootstrap_model <- function(base_model,
 }
 
 
-#' @export
-#' @rdname bootstrap_model
-#' @param suppress_loading_bar
-#' defunct now
-#' @param allow_conv_error
-#' defunct now
-BootGlmm <- function(base_model, # nocov start
-                     resamples = 9999,
-                     base_data = NULL,
-                     return_coefs_instead = FALSE,
-                     resample_specific_blocks = NULL,
-                     unique_resample_lim = NULL,
-                     narrowness_avoid = TRUE,
-                     num_cores = NULL,
-                     suppress_sampling_message = FALSE,
-                     suppress_loading_bar = FALSE,
-                     allow_conv_error = FALSE){
-    .Deprecated("bootstrap_model")
-
-    bootstrap_model(base_model = base_model,
-                    base_data = base_data,
-                    resamples = resamples,
-                    return_coefs_instead = return_coefs_instead,
-                    resample_specific_blocks = resample_specific_blocks,
-                    unique_resample_lim = unique_resample_lim,
-                    narrowness_avoid = narrowness_avoid,
-                    num_cores = num_cores,
-                    suppress_sampling_message = suppress_sampling_message)
-} # nocov end
-
-
 #' Runs the bootstrapping of the models.
 #'
 #' This function gets passed a function that runs a single bootstrap resample
@@ -417,7 +383,8 @@ bootstrap_runner <- function(bootstrap_function,
                                  function(i){
                                      bootstrap_function()
                                  },
-                                 future.packages = future_packages))
+                                 future.packages = future_packages,
+                                 future.seed = TRUE))
     }
 
     if (parallelism == "parallel") {

README.Rmd

@@ -25,7 +25,7 @@ options(warnPartialMatchArgs = FALSE,
 
 ## Overview
 
-glmmboot provides a simple interface for creating bootstrap
+glmmboot provides a simple interface for creating non-parametric bootstrap
 confidence intervals using a wide set of models. The primary function
 is `bootstrap_model`, which has three primary arguments:
 
@@ -47,6 +47,8 @@ For models with random effects:
 
 With no random effects, performs case resampling: resamples each row with replacement.
 
+All of these are considered non-parametric.
+
 ## Requirements:
 
 1. the model should work with the
@@ -88,7 +90,7 @@ devtools::install_github("ColmanHumphrey/glmmboot")
 We'll provide a quick example using glm. First we'll set up some data:
 
 ```{r}
-set.seed(15278086) # Happy for Nadia and Alan
+set.seed(15278086)
 x1 <- rnorm(50)
 x2 <- runif(50)
 
@@ -130,7 +132,8 @@ conservative at `N = 50`.
 
 An example with a zero-inflated model (from the `glmmTMB` docs):
 
-```{r}
+```{r, eval = requireNamespace("glmmTMB", quietly = TRUE)}
+## we'll skip this if glmmTMB not available
 library(glmmTMB)
 
 owls <- transform(Owls,
@@ -148,7 +151,7 @@ fit_zipoisson <- glmmTMB(
 summary(fit_zipoisson)
 ```
 Let's run the bootstrap (ignore the actual results, 3 resamples is basically meaningless - just for illustration):
-```{r}
+```{r, eval = requireNamespace("glmmTMB", quietly = TRUE)}
 zi_results <- bootstrap_model(base_model = fit_zipoisson,
                               base_data = owls,
                               resamples = 3)