check_parameters: parameters checkings

Description

Checks all parameters of the TAD and raises errors if parameters' values are incoherent.

Usage

check_parameters(
  weights = NULL,
  weights_factor = NULL,
  trait_data = NULL,
  randomization_number = NULL,
  aggregation_factor_name = NULL,
  statistics_factor_name = NULL,
  seed = NULL,
  abundance_file = NULL,
  weighted_moments_file = NULL,
  stat_per_obs_file = NULL,
  stat_per_rand_file = NULL,
  stat_skr_param_file = NULL,
  regenerate_abundance_df = NULL,
  regenerate_weighted_moments_df = NULL,
  regenerate_stat_per_obs_df = NULL,
  regenerate_stat_per_rand_df = NULL,
  significativity_threshold = NULL,
  lin_mod = NULL,
  slope_distance = NULL,
  intercept_distance = NULL,
  csv_tsv_load_parameters = NULL
)

Arguments

weights: the dataframe of weights, one row correspond to a series of observation
weights_factor: the dataframe which contains the different factor linked to the weights
trait_data: a vector of the data linked to the different factor
randomization_number: the number of random abundance matrix to generate
aggregation_factor_name: vector of factor name for the generation of random matrix
statistics_factor_name: vector of factor name for the computation of statistics for each generated matrix
seed: the seed of the pseudo random number generator
abundance_file: the path and name of the RDS file to load/save the dataframe which contains the observed data and the generated matrix
weighted_moments_file: the path and name of the RDS file to load/save the dataframe which contains the calculated moments
stat_per_obs_file: the path and name of the RDS file to load/save the dataframe which contains the statistics for each observed row regarding the random ones
stat_per_rand_file: the path and name of the RDS file to load/save the dataframe which contains the statistics for each random matrix generated
stat_skr_param_file: default=NULL You can provide the output to write the SKR statistics results to.
regenerate_abundance_df: boolean to specify if the abundance dataframe is computed again
regenerate_weighted_moments_df: boolean to specify if the weighted moments dataframe is computed again
regenerate_stat_per_obs_df: boolean to specify if the statistics per observation dataframe is computed again
regenerate_stat_per_rand_df: boolean to specify if the statistics per random matrix dataframe is computed again
significativity_threshold: the significance threshold to consider that the observed value is in the randomized value
lin_mod: Indicates the type of linear model to use for (SKR): choose "lm" or "mblm"
slope_distance: slope of the theoretical distribution law (default: slope = 1 intercept = 1.86 skew-uniform distribution family)
intercept_distance: intercept of the theoretical distribution law (default: slope = 1 intercept = 1.86 skew-uniform distribution family)
csv_tsv_load_parameters: a list of parameters for each data structure we want to load. Each element must be named after the data structure we want to load.