aic_tab                 multiScaleR model selection
bic_tab                 multiScaleR model selection
count_data              Example data frame
diagnostics             Retrieve diagnostics from multiScaleR objects
estimate_multiscale_ram
                        Estimate Memory Requirements for Multiscale
                        Optimization
hab                     Example raster
kernel_dist             Scale Distance
kernel_prep             Kernel Scale Preparation
kernel_scale.raster     Apply kernel smoothing to raster layers
landscape               Simulated raster
landscape_counts        Example data frame
msr_vars                Define multiScaleR covariate transformations
multiScaleR-package     multiScaleR
multiScale_optim        Multiscale optimization
plot.multiScaleR        Plot method for multiScaleR objects
plot.sigma_profile      Plot Sigma Profile
plot_kernel             Plot kernel densities
plot_marginal_effects   Plot Marginal Effects from a Fitted Model
print.multiScaleR       Print method for multiScaleR
print.multiScaleR_data
                        Print method for multiScaleR_data
print.summary_multiScaleR
                        Print method for summary_multiScaleR
profile_sigma           Profile Model Fit Across Sigma Parameter Space
pts                     Spatial sample points
sim_dat                 Simulate data for optimizing scales of effect
sim_dat_unmarked        Simulate data for optimizing scales of effect
                        with 'unmarked'
sim_rast                Simulate spatially autocorrelated raster
                        surfaces
summary.multiScaleR     Summarize multiScaleR objects
surv_pts                Spatial sample points
