| predict_ingrowth {MLFS} | R Documentation | 
predict_ingrowth
Description
ingrowth model for predicting new trees within the MLFS
Usage
predict_ingrowth(
  df_fit,
  df_predict,
  site_vars = site_vars,
  include_climate = include_climate,
  eval_model_ingrowth = TRUE,
  k = 10,
  blocked_cv = TRUE,
  ingrowth_model = "glm",
  rf_mtry = NULL,
  ingrowth_table = NULL,
  DBH_distribution_parameters = NULL
)
Arguments
| df_fit | a plot-level data with plotID, stand variables and site descriptors, and the two target variables describing the number of ingrowth trees for inner (ingrowth_3) and outer (ingrowth_15) circles | 
| df_predict | data frame which will be used for ingrowth predictions | 
| site_vars | a character vector of variable names which are used as site descriptors | 
| include_climate | logical, should climate variables be included as predictors | 
| eval_model_ingrowth | logical, should the the ingrowth model be evaluated and returned as the output | 
| k | the number of folds to be used in the k fold cross-validation | 
| blocked_cv | logical, should the blocked cross-validation be used in the evaluation phase? | 
| ingrowth_model | model to be used for ingrowth predictions. 'glm' for generalized linear models (Poisson regression), 'ZIF_poiss' for zero inflated Poisson regression and 'rf' for random forest | 
| rf_mtry | a number of variables randomly sampled as candidates at each split of a random forest model for predicting ingrowth. If NULL, default settings are applied. | 
| ingrowth_table | a data frame with 4 variables: (ingrowth) code, DBH_threshold, DBH_max and weight. Ingrowth table is used within the ingrowth sub model to correctly simulate different ingrowth levels and associated upscale weights | 
| DBH_distribution_parameters | A list with deciles of DBH distributions that are used to simulate DBH for new trees, separately for each ingrowth category | 
Value
a list with four elements:
- $predicted_ingrowth - a data frame with newly added trees based on the ingrowth predictions 
- $eval_ingrowth - a data frame with predicted and observed number of new trees, separately for each ingrowth level, or character string indicating that ingrowth model was not evaluated 
- $mod_ing_3 - the output model for predicting the ingrowth of trees with code 3 
- $mod_ing_15 - the output model for predicting the ingrowth of trees with code 15 (the output name depends on the code used for this particular ingrowth level) 
Examples
library(MLFS)
data(data_v6)
data(data_ingrowth)
data(ingrowth_table)
data(ingrowth_parameter_list)
ingrowth_outputs <- predict_ingrowth(
   df_fit = data_ingrowth,
   df_predict = data_v6,
   site_vars = c("slope", "elevation", "northness", "siteIndex"),
   include_climate = TRUE,
   eval_model_ingrowth = FALSE,
   rf_mtry = 3,
   k = 10, blocked_cv = TRUE,
   ingrowth_model = 'rf',
   ingrowth_table = ingrowth_table,
   DBH_distribution_parameters = ingrowth_parameter_list)