`predict_obs_dens()` performs out-of-sample prediction (separating data into training and test sets). It assumes that training and test sets have the same window.
predict_obs_dens(hfr, ratio, dep_var, indep_var, ngrid = 100, window)list of the following: * `indep_var`: independent variables * `coef`: coefficients * `intens_grid_cells`: im object of observed densities for each time period * `estimated_counts`: the number of events that is estimated by the poisson point process model for each time period * `sum_log_intens`: the sum of log intensities for each time period * `training_row_max`: the max row ID of the training set
hyperframe
numeric. ratio between training and test sets
dependent variables
independent variables
the number of grids. By default, `100`.
owin object