View source: R/abundance_projection.R
| abundance_projection | R Documentation | 
The function projects a number of steps of a time-discrete model, with model parameters taken from a 'cxr_pm_multifit' object or as function arguments.
abundance_projection(
  cxr_fit = NULL,
  model_family = NULL,
  alpha_form = NULL,
  lambda_cov_form = NULL,
  alpha_cov_form = NULL,
  lambda = NULL,
  alpha_matrix = NULL,
  lambda_cov = NULL,
  alpha_cov = NULL,
  covariates = NULL,
  timesteps = 2,
  initial_abundances = 0
)
cxr_fit | 
 object of type 'cxr_pm_multifit'. If this is not specified, all parameters below are needed.  | 
model_family | 
 acronym for model family. Included by default in 'cxr' are 'BH' (Beverton-Holt), 'RK' (Ricker), 'LW' (Law-Watkinson), 'LV' (Lotka-Volterra).  | 
alpha_form | 
 character, either "none","global", or "pairwise".  | 
lambda_cov_form | 
 character, either "none" or "global".  | 
alpha_cov_form | 
 character, either "none","global", or "pairwise".  | 
lambda | 
 named vector with lambda values for all taxa to be projected.  | 
alpha_matrix | 
 square matrix with taxa names in rows and columns.  | 
lambda_cov | 
 optional named matrix with covariates in columns and taxa in rows, representing the effect of each covariate on the lambda parameter of each taxa.  | 
alpha_cov | 
 optional list. Each element of the named list represents the effects of a covariate over alpha values. Thus, each list element contains a square matrix of the same dimensions as 'alpha_matrix', as returned from the function 'cxr_pm_fit'. Note that for alpha_cov_form = "global", all columns in this matrix are the same, as there is a single value per species.  | 
covariates | 
 matrix or dataframe with covariates in columns and timesteps in rows.  | 
timesteps | 
 number of timesteps to project.  | 
initial_abundances | 
 named vector of initial abundances for all taxa.  | 
named matrix with projected abundance values for each taxa at each timestep.
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