Methods for Optimizing Scales of Effect
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Documentation for package ‘multiScaleR’ version 0.7.0
Help Pages
| multiScaleR-package | multiScaleR |
| aic_tab | multiScaleR model selection |
| bic_tab | multiScaleR model selection |
| count_data | Example data frame |
| diagnostics | Retrieve diagnostics from multiScaleR objects |
| diagnostics.multiScaleR | 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 |
| kernel_var | Define multiScaleR covariate transformations |
| landscape | Simulated raster |
| landscape_counts | Example data frame |
| landscape_var | Define multiScaleR covariate transformations |
| msr_vars | Define multiScaleR covariate transformations |
| multiScaleR | 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 |
| surface_var | Define multiScaleR covariate transformations |
| surv_pts | Spatial sample points |