Nothing
## -----------------------------------------------------------------------------
data("fruits_traits", package = "mFD")
knitr::kable(head(fruits_traits),
caption = "Species x traits data frame based on the **fruits** dataset")
## -----------------------------------------------------------------------------
data("baskets_fruits_weights", package = "mFD")
knitr::kable(as.data.frame(baskets_fruits_weights[1:6, 1:6]),
caption = "Species x assemblages matrix based on the **fruits** dataset")
## -----------------------------------------------------------------------------
data("fruits_traits_cat", package = "mFD")
knitr::kable(head(fruits_traits_cat),
caption = "Traits types based on **fruits & baskets** dataset")
## ----echo = FALSE-------------------------------------------------------------
fruits_gower <- mFD::funct.dist(
sp_tr = fruits_traits,
tr_cat = fruits_traits_cat,
metric = "gower",
scale_euclid = "noscale",
ordinal_var = "classic",
weight_type = "equal",
stop_if_NA = TRUE)
## -----------------------------------------------------------------------------
baskets_FD2max <- mFD::alpha.fd.hill(
asb_sp_w = baskets_fruits_weights,
sp_dist = fruits_gower,
tau = "max",
q = 2)
## -----------------------------------------------------------------------------
baskets_FD2mean <- mFD::alpha.fd.hill(
asb_sp_w = baskets_fruits_weights,
sp_dist = fruits_gower,
tau = "mean",
q = 2)
## -----------------------------------------------------------------------------
round(cbind(FD2max = baskets_FD2max$"asb_FD_Hill"[ , 1],
FD2mean = baskets_FD2mean$"asb_FD_Hill"[ , 1]), 2)
## -----------------------------------------------------------------------------
# Retrieve species occurrences data:
baskets_summary <- mFD::asb.sp.summary(baskets_fruits_weights)
baskets_fruits_occ <- baskets_summary$"asb_sp_occ"
head(baskets_fruits_occ)
# Compute alpha FD Hill with q = 0:
baskets_FD0mean <- mFD::alpha.fd.hill(
asb_sp_w = baskets_fruits_occ,
sp_dist = fruits_gower,
tau = "mean",
q = 0)
round(baskets_FD0mean$"asb_FD_Hill", 2)
## -----------------------------------------------------------------------------
# retrieve total weight per basket:
baskets_summary$"asb_tot_w"
# Here baskets all contain 2000g of fruits, we illustrate how to compute...
# relative weights using the output of asb.sp.summary:
baskets_fruits_relw <- baskets_fruits_weights / baskets_summary$"asb_tot_w"
apply(baskets_fruits_relw, 1, sum)
## -----------------------------------------------------------------------------
# Compute index:
baskets_betaq2 <- mFD::beta.fd.hill(
asb_sp_w = baskets_fruits_relw,
sp_dist = fruits_gower,
q = 2,
tau = "mean",
beta_type = "Jaccard")
# Then use the mFD::dist.to.df function to ease visualizing result
mFD::dist.to.df(list_dist = list("FDq2" = baskets_betaq2$"beta_fd_q"$"q2"))
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