Calibrate_model: Calibrate vegetation distribution models

In MartinezLaura/CanHeMonR.MaxEnt: Application of MaxEnt for canopy health monitoring through airbone image analysis.

Description

For each class in .shp polygon file, calibrate a distribution model using a raster brick as predictors.

Usage

Calibrate_model(vuln_classes = "ALL", training_path, model_outp_dir, name,
  stadistics = FALSE, myargs = NULL, model_type, stadisticspath = NULL)

Arguments

vuln_classes	A character vector of the classes you want to model. The should be presented in the column 'class' of training_df. Default 'ALL'
training_path	Path to the rdsdata that contains the data.frame, with in the column 'pres' 1/0 to indicate presence absence, then covariate columns, and a colum 'class' groupin grows by the land-cover class the data was sampled for. This df is typically generated by sample_points.r
model_outp_dir	Path and filename prefix to save the model objects
name	Character. Name that you want to give to the serialized object with the model
stadistics	Boolean. If Ture stadistics of the model will be done and save. Take into account that it can take several time. Default FALSE
myargs	List. Arguments to pass to the maxent model, in the following format. Example: myargs <- c("noautofeature", "nohinge", "nothreshold", "noproduct","nolinear"). Default NULL
model_type	Character. Type of model that we wnat to use to predict types: raw - logistic - cloglog
stadisticspath	Path where you want to save the stadistics of the model. Default NULL

Value

Serialized object with class-specific distribution models, using a data frame created from training points and covariate images

See Also

For more possible arguments for MaxEnt see: https://groups.google.com/forum/#!msg/Maxent/yRBlvZ1_9rQ/Fj8Two0lmHIJ

Depends on: sick_tree_errors.r

Examples

## Not run: 
tt <- calibrate_model(vuln_classes = list(c('Pb')), 
                      training_path = '/DATA/Results/RunSickTree_Output/ADS/Test/MaxentModel/MaxentCastelobranco_NA-buffer.rdsdata',
                      model_outp_dir = '/DATA/Results/RunSickTree_Output/ADS/Final_Iter1-2/MaxentModel/',
                      name='samp_NA_buffer_logistic', 
                      stadistics = TRUE,
                      myargs = c("noautofeature", "nohinge"),
                      model_type = 'cloglog',
                      stadisticspath = '/DATA/Results/RunSickTree_Output/ADS/Test/MaxentModel/Stadistics/')
                      
## End(Not run)

MartinezLaura/CanHeMonR.MaxEnt documentation built on May 17, 2019, 6:21 p.m.