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)
} # }