Update "no visible bindings"

NAMESPACE

@@ -23,6 +23,7 @@ import(parallel)
 import(plyr, except = c(failwith, id, summarize, count, desc, mutate, arrange, rename, is.discrete, summarise, summarize))
 import(tidyr, except = extract)
 importFrom(stats,approx)
+importFrom(stats,embed)
 importFrom(stats,median)
 importFrom(stats,pnorm)
 importFrom(stats,qnorm)

R/growth.R

@@ -165,6 +165,13 @@ cleangrowth <- function(subjid,
   z.orig_cdc <- z.orig_who <- sd.orig_cdc <- sd.orig_who <- NULL
   result <- NULL
 
+  sd.orig_uncorr <- agemonths <- intwt <- fengadays <- pmagedays <- cagedays <-
+    unmod_zscore <- fen_wt_m <- fen_wt_l <- fen_wt_s <- cwho_cv <- ccdc_cv <-
+    sd.c_cdc <- sd.c_who <- sd.c <- sd.corr <- seq_win <- sd.corr_abssumdiff <-
+    sd.orig_abssumdiff <- ..orig_colnames <- ctbc.sd <- sum_sde <- no_sde <-
+    sum_val <- no_dup_val <- no_outliers <- no_bigdiff <- nottoofar <- nnte <-
+    nnte_full <- NULL
+
   # preprocessing ----
 
   # organize data into a dataframe along with a line "index" so the original data order can be recovered

R/infants_clean.R

@@ -15,7 +15,7 @@
 #'
 #' @keywords internal
 #' @import data.table
-#' @importFrom stats median
+#' @importFrom stats median embed
 #' @noRd
 cleanbatch_infants <- function(data.df,
                                log.path,
@@ -58,6 +58,22 @@ cleanbatch_infants <- function(data.df,
 
   oob <- sd_med <- med_diff <- max_diff <- sum_oob <- i.exclude <- NULL
 
+
+  # avoid no visible warning errors
+  sum_sde <- no_sde <- cf <- wholehalfimp <- seq_win <- cs <- absdiff <-
+    sd.orig_uncorr <- seq_win <- absdiff <- wholehalfimp <- ageyears <- ctbc.sd <-
+    ..col_replace <- c.ewma.all <- pot_excl <- c.dewma.all <- p_plus <-
+    p_minus <- ctbc.sd <- c.ewma.all <- tbc_diff_next <- tbc_diff_prior <-
+    tbc_diff_plus_next <- tbc.p_plus <- tbc_diff_plus_prior <-
+    tbc_diff_minus_next <- tbc.p_minus <- tbc_diff_minus_prior <- addcrithigh <-
+    addcritlow <- tbc_dop <- i.tbc.sd <- rowind <- abssum <- c.dewma.all <-
+    whoagegrp_ht <- d_agedays <- mindiff <- maxdiff <- who_mindiff_ht <-
+    who_maxdiff_ht <- mindiff_prev <- maxdiff_prev <- whoinc.age.hc <-
+    who_maxdiff_hc <- who_mindiff_hc <- diff_prev <-
+    diff_next <- aft.g.aftm1 <- val_excl <-
+    absval <- comp_diff <- err_ratio <-
+    NULL
+
   data.df <- data.table(data.df, key = c('subjid', 'param', 'agedays', 'index'))
 
   if (parallel & !is.na(log.path)) {

R/infants_support.R

@@ -154,6 +154,10 @@ calc_oob_evil_twins <- function(df){
 #' @keywords internal
 #' @noRd
 calc_and_recenter_z_scores <- function(df, cn, ref.data.path){
+  # avoid no visible warning errors
+  cn.orig_cdc <- param <- agedays <- sex <- cn.orig_who <- cn.orig <- subjid <-
+    tbc.cn <- sd.median <- NULL
+
   # for infants, use z and who
   measurement.to.z <- read_anthro(ref.data.path, cdc.only = TRUE,
                                   infants = TRUE)