#' @import dplyr
calc_tendances <- function(df, quantite, group = NULL) {
df <- rename(df, Q = !!quantite)
calc_senslope <- function(df2, ...) {
df2 <- filter(df2, !is.na(Q))
if (nrow(df) >= 3) {
sen_slope <- arrange(df2, annee) %>%
pull(Q) %>%
trend::sens.slope()
tibble(pente = sen_slope$estimate,
p_value = sen_slope$p.value) %>%
mutate(intercept = median(df2$Q - pente * df2$annee))
} else {
tibble(pente = NA_real_,
p_value = NA_real_,
intercept = NA_real_)
}
}
group_by_at(df, .vars = c(group, "substance")) %>%
group_modify(.f = calc_senslope) %>%
ungroup() %>%
filter(!is.na(pente))
}
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