fit_gam: fit_gam fit a Generalized Additive Model to butterfly count...

In RetoSchmucki/rbms: Computing generalised abundance indices for butterfly monitoring count data

fit_gam fit a Generalized Additive Model to butterfly count data along a temporal variable and accounting for site effect when multiple are available.

Description

fit_gam fit a Generalized Additive Model to butterfly count data along a temporal variable and accounting for site effect when multiple are available.

Usage

fit_gam(
  dataset_y,
  NbrSample = NULL,
  GamFamily = "poisson",
  MaxTrial = 4,
  SpeedGam = TRUE,
  OptiGam = TRUE,
  TimeUnit = "d",
  MultiVisit = "mean",
  weekday = 3,
  mod_form = NULL,
  tp_col = NULL,
  verbose = TRUE,
  ...
)

Arguments

dataset_y	data.table Filtered butterfly counts for species x over year y over all sites.
NbrSample	integer Inherited from flight_curve, default=100.
GamFamily	string Inherited from flight_curve, default='poisson', but can be 'nb' or 'quasipoisson'.
MaxTrial	integer Inherited from flight_curve, default=3.
SpeedGam	logical to use the bam method instead of the gam method.
OptiGam	logical Set if the bam method should be used, default instead of the default gam method.
TimeUnit	character The time-step for which the spline should be computed, 'd' day or 'w' week.
MultiVisit	string Function to apply for summarising multiple counts within a time unit, 'max' or 'mean' (default).
weekday	Integer for selected day of the week for weekly summary, default is 3 (Wednesday). [1-7] where 1 = Monday.
mod_form	string with formula to be passed to the gam model, default null.
tp_col	string or vector of string with additional variable used in the gam model, default null.
verbose	a logical indicating if some “progress report” should be given.
...	Additional parameters passed to gam or bam function from the gam package.

Value

A list with three objects, i) **f_curve**: a data.table with the flight curve f_curve with expected relative abundance, normalize to sum to one over a full season, ii) **f_model**: the resulting gam model f_model fitted on the count data and iii) **f_data**: a data.table with the data used to fit the GAM model. This is provide for one year 'y'.

Author(s)

Reto Schmucki - [e-mail]

See Also

flight_curve, gam, bam

RetoSchmucki/rbms documentation built on Feb. 14, 2024, 3:17 a.m.