Package index
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dist_decay()
threshold_decay()
step_decay()
bartlett_decay()
tent_decay()
linear_decay()
gaussian_decay()
half_norm_decay()
exp_decay()
- Zone of Influence (ZOI) functions
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plot_zoi1d()
- Plot the functions for the nearest and cumulative zone of influence in 1 dimension
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calc_zoi()
- Calculates the zone of influence from the nearest feature and the cumulative zone of influence of multiple features
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calc_zoi_cumulative()
- Calculate the cumulative zone of influence of multiple features
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calc_zoi_nearest()
- Calculate the zone of influence from the nearest feature
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calc_zoi_sql()
- Compute Zone of Influence for points and annotate them to points using SQL
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filter_create()
- Create filters or kernel matrices for raster neighborhood analyses
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filter_na_strata()
- Remove missing values and ensure case-control per stratum
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filter_save()
- Save kernel/filter matrix to use outside R
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add_zoi_formula()
- Adds ZOI radii to formula
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add_zoi_layers()
- Create ZOI layer names as strings for data annotation
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explore_blocks()
- Explore hierarchical blocks after sampling or spatial stratification
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explore_blocks_pre()
- Explore potential hierarchical blocks before sampling or spatial stratification
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spat_strat()
- Preparing data for spatially stratified cross‐validation schemes
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create_resamples()
- Create samples for fitting, calibrating, and validating models
Estimating ZOI - fit models
Functions to fit RSF and SSF and estimate ZOI using penalized regression
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filter_na_strata()
- Remove missing values and ensure case-control per stratum
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extract_response_strata()
- Separates elements in a statistical formula
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net_clogit()
net_ssf()
net_issf()
- Fits a conditional logistic regression/SSF/iSSF using glmnet
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net_logit()
net_rsf()
- Fits a logistic regression/RSF using glmnet
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fit_net_clogit()
fit_net_ssf()
fit_net_issf()
- Fits a conditional logistic regression/SSF/iSSF with penalized regression using glmnet in a train-validate-test setup
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fit_net_logit()
fit_net_rsf()
- Fit logistic regression/RSF with penalized regression using glmnet in a train-validate-test setup
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bag_fit_net_clogit()
- Fit a bag of conditional logistic regression/SSF/iSSF models with penalized regression in a train-validate-test setup
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bag_fit_net_logit()
- Fit a bag of logistic regression/RSF models with penalized regression in a train-validate-test setup
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bag_load_models()
- Load a series of files output of fit_net_clogit models and put them on a bag
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bag_models()
w_strech_maxmin_squared()
w_strech_max_squared()
score2weight_mean()
score2weight_min_mean()
score2weight_invmean()
score2weight_min_invmean()
- Summary of a bag of models
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conditionalBoyce()
conditionalSomersD()
conditionalAUC()
AUC()
coxnet.deviance()
Cindex()
- Computes the conditional Boyce index for model evaluation
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kernel_prediction()
- Prediction based only on step length terms
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pretty_seq()
- Set sampling parameters
Estimating ZOI - interpret and visualize models
Functions to help interpreting parameters and visualizing cumulative impacts
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bag_predict()
- Prediction of a bag of models to new data
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plot_importance()
- Plot variable importance
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variable_importance()
- Computes variable importance
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plot_coef()
- Plot the coefficients of bags of models
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plot_response()
- Plot responses from a bag of models
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bag_predict_spat()
bag_predict_spat_vars()
- Predict bag of models in space
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rescale_coefficients()
- Rescale standardized coefficients back to their original range after model fitting
Raster processing ancillary functions
GRASS GIS ancillary functions to process rasters and prepare inputs for computing zones of influence
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grass_binarize()
- Binarize continuous raster maps
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grass_find_layer()
- Find layers within GRASS GIS with multiple patterns
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grass_v2rast_count()
- Rasterizes a vector counting the number of features in each pixel
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raster_rescale()
- Rescale raster values
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set_points()
- Simulate points in a landscape
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set_points_from_raster()
- Simulate points using input raster as weights
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set_points_sample()
- Simulate regular or random points in 2D
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isolation()
mean_isolation()
- Isolation and mean isolation of points in space
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reindeer
- GPS positions for wild reindeer in Norway.
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reindeer_area.gpkg
- Reindeer area: a polygon vector data for the Setesdal Austhei reindeer herding area
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reindeer_cabins.gpkg
- Cabins vector data for the reindeer area
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reindeer_roads_private.gpkg
- Private roads vector data for the reindeer area
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reindeer_roads_public.gpkg
- Public roads vector data for the reindeer area
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reindeer_rsf
- Annotated data of wild reindeer in Norway, prepared for point resource-selection analysis.
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reindeer_ssf
- Annotated data of wild reindeer in Norway, prepared for step-selection analysis.
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sample_area_cabins.tif
- Cabin presence raster data for the sample area
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sample_area_cabins_count.tif
- Cabin count raster data for the sample area
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sample_area_roads.tif
- Road raster data for the sample area
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sample_area.gpkg
- Sample area: a polygon vector data
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sample_area_cabins.gpkg
- Cabins vector data for the sample area
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sample_area_roads.gpkg
- Road vector data for the sample area