lintr

R/bci.R

@@ -47,7 +47,8 @@ bci.numeric <- function(x, ci = 0.95, verbose = TRUE, ...) {
 bci.data.frame <- function(x, ci = 0.95, rvar_col = NULL, verbose = TRUE, ...) {
   obj_name <- insight::safe_deparse_symbol(substitute(x))
 
-  if (length(x_rvar <- .possibly_extract_rvar_col(x, rvar_col)) > 0L) {
+  x_rvar <- .possibly_extract_rvar_col(x, rvar_col)
+  if (length(x_rvar) > 0L) {
     cl <- match.call()
     cl[[1]] <- bayestestR::bci
     cl$x <- x_rvar

R/ci.R

@@ -160,7 +160,8 @@ ci.numeric <- function(x, ci = 0.95, method = "ETI", verbose = TRUE, BF = 1, ...
 #' @inheritParams p_direction
 #' @export
 ci.data.frame <- function(x, ci = 0.95, method = "ETI", BF = 1, rvar_col = NULL, verbose = TRUE, ...) {
-  if (length(x_rvar <- .possibly_extract_rvar_col(x, rvar_col)) > 0L) {
+  x_rvar <- .possibly_extract_rvar_col(x, rvar_col)
+  if (length(x_rvar) > 0L) {
     cl <- match.call()
     cl[[1]] <- bayestestR::ci
     cl$x <- x_rvar

R/describe_posterior.R

@@ -465,7 +465,7 @@ describe_posterior.default <- function(posterior, ...) {
     test_psig$.rowid <- seq_len(nrow(test_psig))
   } else if (!all(is.na(test_rope$Parameter))) {
     test_rope$.rowid <- seq_len(nrow(test_rope))
-  } else if (!all(is.na(test_bf$Parameter))) {
+  } else if (!all(is.na(test_bf$Parameter))) { # nolint
     test_bf$.rowid <- seq_len(nrow(test_bf))
   } else {
     estimates$.rowid <- seq_len(nrow(estimates))
@@ -590,12 +590,14 @@ describe_posterior.data.frame <- function(posterior,
                                           rvar_col = NULL,
                                           verbose = TRUE,
                                           ...) {
-  if (length(x_rvar <- .possibly_extract_rvar_col(posterior, rvar_col)) > 0L) {
+  x_rvar <- .possibly_extract_rvar_col(posterior, rvar_col)
+  if (length(x_rvar) > 0L) {
     cl <- match.call()
     cl[[1]] <- bayestestR::describe_posterior
     cl$posterior <- x_rvar
     cl$rvar_col <- NULL
-    if (length(prior_rvar <- .possibly_extract_rvar_col(posterior, bf_prior)) > 0L) {
+    prior_rvar <- .possibly_extract_rvar_col(posterior, bf_prior)
+    if (length(prior_var) > 0L) {
       cl$bf_prior <- prior_rvar
     }
     out <- eval.parent(cl)

R/equivalence_test.R

@@ -150,7 +150,8 @@ equivalence_test.numeric <- function(x, range = "default", ci = 0.95, verbose =
 equivalence_test.data.frame <- function(x, range = "default", ci = 0.95, rvar_col = NULL, verbose = TRUE, ...) {
   obj_name <- insight::safe_deparse_symbol(substitute(x))
 
-  if (length(x_rvar <- .possibly_extract_rvar_col(x, rvar_col)) > 0L) {
+  x_rvar <- .possibly_extract_rvar_col(x, rvar_col)
+  if (length(x_rvar) > 0L) {
     cl <- match.call()
     cl[[1]] <- bayestestR::equivalence_test
     cl$x <- x_rvar

R/estimate_density.R

@@ -235,7 +235,8 @@ estimate_density.data.frame <- function(x,
                                         at = NULL,
                                         rvar_col = NULL,
                                         ...) {
-  if (length(x_rvar <- .possibly_extract_rvar_col(x, rvar_col)) > 0L) {
+  x_rvar <- .possibly_extract_rvar_col(x, rvar_col)
+  if (length(x_rvar) > 0L) {
     cl <- match.call()
     cl[[1]] <- bayestestR::estimate_density
     cl$x <- x_rvar

R/eti.R

@@ -71,7 +71,8 @@ eti.numeric <- function(x, ci = 0.95, verbose = TRUE, ...) {
 eti.data.frame <- function(x, ci = 0.95, rvar_col = NULL, verbose = TRUE, ...) {
   obj_name <- insight::safe_deparse_symbol(substitute(x))
 
-  if (length(x_rvar <- .possibly_extract_rvar_col(x, rvar_col)) > 0L) {
+  x_rvar <- .possibly_extract_rvar_col(x, rvar_col)
+  if (length(x_rvar) > 0L) {
     cl <- match.call()
     cl[[1]] <- bayestestR::eti
     cl$x <- x_rvar

R/hdi.R

@@ -148,7 +148,8 @@ hdi.numeric <- function(x, ci = 0.95, verbose = TRUE, ...) {
 hdi.data.frame <- function(x, ci = 0.95, rvar_col = NULL, verbose = TRUE, ...) {
   obj_name <- insight::safe_deparse_symbol(substitute(x))
 
-  if (length(x_rvar <- .possibly_extract_rvar_col(x, rvar_col)) > 0L) {
+  x_rvar <- .possibly_extract_rvar_col(x, rvar_col)
+  if (length(x_rvar) > 0L) {
     cl <- match.call()
     cl[[1]] <- bayestestR::hdi
     cl$x <- x_rvar

R/map_estimate.R

@@ -151,7 +151,8 @@ map_estimate.brmsfit <- function(x, precision = 2^10, method = "kernel", effects
 #' @inheritParams p_direction
 #' @export
 map_estimate.data.frame <- function(x, precision = 2^10, method = "kernel", rvar_col = NULL, ...) {
-  if (length(x_rvar <- .possibly_extract_rvar_col(x, rvar_col)) > 0L) {
+  x_rvar <- .possibly_extract_rvar_col(x, rvar_col)
+  if (length(x_rvar) > 0L) {
     cl <- match.call()
     cl[[1]] <- bayestestR::map_estimate
     cl$x <- x_rvar

R/p_map.R

@@ -127,7 +127,8 @@ p_map.get_predicted <- function(x,
 #' @rdname p_map
 #' @inheritParams p_direction
 p_map.data.frame <- function(x, null = 0, precision = 2^10, method = "kernel", rvar_col = NULL, ...) {
-  if (length(x_rvar <- .possibly_extract_rvar_col(x, rvar_col)) > 0L) {
+  x_rvar <- .possibly_extract_rvar_col(x, rvar_col)
+  if (length(x_rvar) > 0L) {
     cl <- match.call()
     cl[[1]] <- bayestestR::p_map
     cl$x <- x_rvar

R/p_significance.R

@@ -114,7 +114,8 @@ p_significance.get_predicted <- function(x,
 p_significance.data.frame <- function(x, threshold = "default", rvar_col = NULL, ...) {
   obj_name <- insight::safe_deparse_symbol(substitute(x))
 
-  if (length(x_rvar <- .possibly_extract_rvar_col(x, rvar_col)) > 0L) {
+  x_rvar <- .possibly_extract_rvar_col(x, rvar_col)
+  if (length(x_rvar) > 0L) {
     cl <- match.call()
     cl[[1]] <- bayestestR::p_significance
     cl$x <- x_rvar
@@ -269,18 +270,18 @@ p_significance.stanreg <- function(x,
   component <- match.arg(component)
   threshold <- .select_threshold_ps(model = x, threshold = threshold, verbose = verbose)
 
-  data <- p_significance(
+  result <- p_significance(
     insight::get_parameters(x, effects = effects, component = component, parameters = parameters),
     threshold = threshold
   )
 
   cleaned_parameters <- insight::clean_parameters(x)
-  out <- .prepare_output(data, cleaned_parameters, inherits(x, "stanmvreg"))
+  out <- .prepare_output(result, cleaned_parameters, inherits(x, "stanmvreg"))
 
   attr(out, "clean_parameters") <- cleaned_parameters
   attr(out, "threshold") <- threshold
   attr(out, "object_name") <- insight::safe_deparse_symbol(substitute(x))
-  class(out) <- class(data)
+  class(out) <- class(result)
 
   out
 }
@@ -305,18 +306,18 @@ p_significance.brmsfit <- function(x,
   component <- match.arg(component)
   threshold <- .select_threshold_ps(model = x, threshold = threshold, verbose = verbose)
 
-  data <- p_significance(
+  result <- p_significance(
     insight::get_parameters(x, effects = effects, component = component, parameters = parameters),
     threshold = threshold
   )
 
   cleaned_parameters <- insight::clean_parameters(x)
-  out <- .prepare_output(data, cleaned_parameters)
+  out <- .prepare_output(result, cleaned_parameters)
 
   attr(out, "clean_parameters") <- cleaned_parameters
   attr(out, "threshold") <- threshold
   attr(out, "object_name") <- insight::safe_deparse_symbol(substitute(x))
-  class(out) <- class(data)
+  class(out) <- class(result)
 
   out
 }

R/point_estimate.R

@@ -83,7 +83,7 @@ point_estimate.numeric <- function(x, centrality = "all", dispersion = FALSE, th
     estimate_list <- centrality
   }
 
-  out <- data.frame(".temp" = 0)
+  out <- data.frame(.temp = 0)
 
   # Median
   if ("median" %in% estimate_list) {
@@ -132,8 +132,14 @@ point_estimate.numeric <- function(x, centrality = "all", dispersion = FALSE, th
 #' @export
 #' @rdname point_estimate
 #' @inheritParams p_direction
-point_estimate.data.frame <- function(x, centrality = "all", dispersion = FALSE, threshold = 0.1, rvar_col = NULL, ...) {
-  if (length(x_rvar <- .possibly_extract_rvar_col(x, rvar_col)) > 0L) {
+point_estimate.data.frame <- function(x,
+                                      centrality = "all",
+                                      dispersion = FALSE,
+                                      threshold = 0.1,
+                                      rvar_col = NULL,
+                                      ...) {
+  x_rvar <- .possibly_extract_rvar_col(x, rvar_col)
+  if (length(x_rvar) > 0L) {
     cl <- match.call()
     cl[[1]] <- bayestestR::point_estimate
     cl$x <- x_rvar
@@ -156,7 +162,7 @@ point_estimate.data.frame <- function(x, centrality = "all", dispersion = FALSE,
     estimates <- do.call(rbind, estimates)
   }
 
-  out <- cbind(data.frame("Parameter" = names(x), stringsAsFactors = FALSE), estimates)
+  out <- cbind(data.frame(Parameter = names(x), stringsAsFactors = FALSE), estimates)
   rownames(out) <- NULL
   attr(out, "data") <- x
   attr(out, "centrality") <- centrality
@@ -209,7 +215,11 @@ point_estimate.BGGM <- point_estimate.bcplm
 
 
 #' @export
-point_estimate.bamlss <- function(x, centrality = "all", dispersion = FALSE, component = c("conditional", "location", "all"), ...) {
+point_estimate.bamlss <- function(x,
+                                  centrality = "all",
+                                  dispersion = FALSE,
+                                  component = c("conditional", "location", "all"),
+                                  ...) {
   component <- match.arg(component)
   out <- point_estimate(
     insight::get_parameters(x, component = component),

R/print.equivalence_test.R

@@ -84,7 +84,7 @@ print.equivalence_test <- function(x, digits = 2, ...) {
 
 
 .dynGet <- function(x,
-                    ifnotfound = stop(gettextf("%s not found", sQuote(x)), domain = NA),
+                    ifnotfound = stop(gettextf("%s not found", sQuote(x)), domain = NA, call. = FALSE),
                     minframe = 1L,
                     inherits = FALSE) {
   x <- insight::safe_deparse(x)

R/rope.R

@@ -219,7 +219,8 @@ rope.get_predicted <- function(x,
 rope.data.frame <- function(x, range = "default", ci = 0.95, ci_method = "ETI", rvar_col = NULL, verbose = TRUE, ...) {
   obj_name <- insight::safe_deparse_symbol(substitute(x))
 
-  if (length(x_rvar <- .possibly_extract_rvar_col(x, rvar_col)) > 0L) {
+  x_rvar <- .possibly_extract_rvar_col(x, rvar_col)
+  if (length(x_rvar) > 0L) {
     cl <- match.call()
     cl[[1]] <- bayestestR::rope
     cl$x <- x_rvar

R/si.R

@@ -224,12 +224,14 @@ si.get_predicted <- function(posterior, prior = NULL, BF = 1, use_iterations = F
 #' @inheritParams p_direction
 #' @export
 si.data.frame <- function(posterior, prior = NULL, BF = 1, rvar_col = NULL, verbose = TRUE, ...) {
-  if (length(x_rvar <- .possibly_extract_rvar_col(posterior, rvar_col)) > 0L) {
+  x_rvar <- .possibly_extract_rvar_col(posterior, rvar_col)
+  if (length(x_rvar) > 0L) {
     cl <- match.call()
     cl[[1]] <- bayestestR::si
     cl$posterior <- x_rvar
     cl$rvar_col <- NULL
-    if (length(prior_rvar <- .possibly_extract_rvar_col(posterior, prior)) > 0L) {
+    prior_rvar <- .possibly_extract_rvar_col(posterior, prior)
+    if (length(prior_rvar) > 0L) {
       cl$prior <- prior_rvar
     }
     out <- eval.parent(cl)

R/spi.R

@@ -71,7 +71,8 @@ spi.numeric <- function(x, ci = 0.95, verbose = TRUE, ...) {
 spi.data.frame <- function(x, ci = 0.95, rvar_col = NULL, verbose = TRUE, ...) {
   obj_name <- insight::safe_deparse_symbol(substitute(x))
 
-  if (length(x_rvar <- .possibly_extract_rvar_col(x, rvar_col)) > 0L) {
+  x_rvar <- .possibly_extract_rvar_col(x, rvar_col)
+  if (length(x_rvar) > 0L) {
     cl <- match.call()
     cl[[1]] <- bayestestR::spi
     cl$x <- x_rvar
@@ -351,11 +352,7 @@ spi.get_predicted <- function(x, ci = 0.95, use_iterations = FALSE, verbose = TR
   }
 
   # output
-  data.frame(
-    "CI" = ci,
-    "CI_low" = x.l,
-    "CI_high" = x.u
-  )
+  data.frame(CI = ci, CI_low = x.l,CI_high = x.u)
 }
 
 .spi_lower <- function(bw, n.sims, k, l, dens, x) {
@@ -432,7 +429,7 @@ spi.get_predicted <- function(x, ci = 0.95, use_iterations = FALSE, verbose = TR
   w.l <- quadprog::solve.QP(D.l, d.l, A.l, c(1, rep(0, range_ll_lu + 2)), range_ll_lu)
   x.l <- w.l$solution %*% x[l.l:l.u]
 
-  return(x.l)
+  x.l
 }
 
 .spi_upper <- function(bw, n.sims, ui, u, dens, x) {

R/utils.R

@@ -186,21 +186,21 @@
   all_attrs <- attributes(results) # save attributes for later
   all_class <- class(results)
 
-  grid <- insight::get_datagrid(object)
-  grid_names <- colnames(grid)
+  datagrid <- insight::get_datagrid(object)
+  grid_names <- colnames(datagrid)
 
   if (long) {
-    grid$Parameter <- unique(results$Parameter)
-    results <- datawizard::data_merge(grid, results, by = "Parameter")
+    datagrid$Parameter <- unique(results$Parameter)
+    results <- datawizard::data_merge(datagrid, results, by = "Parameter")
     results$Parameter <- NULL
     class(results) <- all_class
   } else {
-    results[colnames(grid)] <- grid
+    results[colnames(datagrid)] <- datagrid
     results$Parameter <- NULL
     results <- results[, c(grid_names, setdiff(colnames(results), grid_names)), drop = FALSE]
 
     # add back attributes
-    most_attrs <- all_attrs[setdiff(names(all_attrs), names(attributes(grid)))]
+    most_attrs <- all_attrs[setdiff(names(all_attrs), names(attributes(datagrid)))]
     attributes(results)[names(most_attrs)] <- most_attrs
   }
 
@@ -225,13 +225,13 @@
   all_attrs <- attributes(results) # save attributes for later
   all_class <- class(results)
 
-  is_rvar <- vapply(object, function(col) inherits(col, "rvar"), FUN.VALUE = logical(1))
+  is_rvar <- vapply(object, inherits, FUN.VALUE = logical(1), "rvar")
   grid_names <- colnames(object)[!is_rvar]
-  grid <- data.frame(object[, grid_names, drop = FALSE])
+  datagrid <- data.frame(object[, grid_names, drop = FALSE])
 
   if (long) {
-    grid$Parameter <- unique(results$Parameter)
-    results <- datawizard::data_merge(grid, results, by = "Parameter")
+    datagrid$Parameter <- unique(results$Parameter)
+    results <- datawizard::data_merge(datagrid, results, by = "Parameter")
     results$Parameter <- NULL
     class(results) <- all_class
   } else {