Run multiple Zeta.msgdm ispline models and return both models and combined ispline table

Fits Zeta.msgdm models of type “ispline” for a series of zeta-orders, extracts the raw environmental covariates (plus distance) and their ispline bases, and returns both the list of fitted models and one tidy data frame combining all orders.

Usage

run_ispline_models(
  spp_df,
  env_df,
  xy_df,
  orders = 2:6,
  sam = 100,
  distance.type = "Euclidean",
  normalize = "Jaccard",
  reg_type = "ispline"
)

Arguments

spp_df

A data frame or matrix of species incidence/abundance.

env_df

A data frame of environmental covariates.

xy_df

A two-column data frame or matrix of site coordinates.

orders

Integer vector of zeta orders to fit (e.g. 2:6).

sam

Integer; number of random samples per order (passed to Zeta.msgdm).

distance.type

Character; distance metric for Zeta.msgdm (default “Euclidean”).

normalize

Character; normalization method for Zeta.msgdm (default “Jaccard”).

reg_type

Character; regression type for Zeta.msgdm (default “ispline”).

Value

A named list with:

zeta_gdm_list

A list of the fitted Zeta.msgdm() objects, named by order.

ispline_table

A tibble with one row per sample, containing all original covariates (including distance), the ispline bases suffixed _is, and a zOrder column.

See also

Zeta.msgdm, Return.ispline

Examples

if (FALSE) { # \dontrun{
data(bird.spec.fine); data(bird.env.fine)
xy   <- bird.spec.fine[,1:2]
spp  <- bird.spec.fine[,3:102]
env  <- bird.env.fine[,3:9]

out <- run_ispline_models(
  spp_df        = spp,
  env_df        = env,
  xy_df         = xy,
  orders        = 2:6,
  sam           = 100,
  normalize     = "Jaccard",
  reg_type      = "ispline"
)
names(out)
head(out$ispline_table)
} # }