R: Auto Visual Inference with Computer Vision Models

# Auto Visual Inference with Computer Vision Models

## Documentation for package ‘autovi’ version 0.4.1

- DESCRIPTION file
- Package NEWS
- Package README

## Help Pages

AUTO_VI | AUTO_VI class environment
auto_vi | AUTO_VI class environment
AUTO_VI$..init.. | Initialization method
AUTO_VI$..str.. | String representation of the object
AUTO_VI$auxiliary | Compute auxiliary variables for the keras model
AUTO_VI$boot_method | Get bootstrapped residuals from a fitted model
AUTO_VI$boot_vss | Predict visual signal strength for bootstrapped residual plots
AUTO_VI$check | Conduct a auto visual inference check with a computer vision model
AUTO_VI$check_result | List of diagnostic results
AUTO_VI$feature_pca | Conduct principal component analysis for features extracted from keras model
AUTO_VI$feature_pca_plot | Draw a summary Plot for principal component analysis conducted on extracted features
AUTO_VI$get_data | Get data out of a model object
AUTO_VI$get_fitted_and_resid | Get fitted values and residuals out of a model object
AUTO_VI$likelihood_ratio | Compute the likelihood ratio using the simulated result
AUTO_VI$lineup_check | Conduct a auto visual inference lineup check with a computer vision model
AUTO_VI$null_method | Get null residuals from a fitted model
AUTO_VI$null_vss | Simulate null plots and predict the visual signal strength
AUTO_VI$plot_lineup | Draw a lineup of standard residual plots
AUTO_VI$plot_pair | Draw a pair of standard residual plots
AUTO_VI$plot_resid | Draw a standard residual plot
AUTO_VI$p_value | Compute the p-value based on the check result
AUTO_VI$rotate_resid | Get rotated residuals from a fitted linear model
AUTO_VI$save_plot | Save plot(s)
AUTO_VI$summary | Summary of the object
AUTO_VI$summary_density_plot | Draw a summary density plot for the result
AUTO_VI$summary_plot | Draw a summary plot for the result
AUTO_VI$summary_rank_plot | Draw a summary rank plot for the result
AUTO_VI$vss | Predict the visual signal strength
check_python_library_available | Check python library availability
get_keras_model | Download and load the keras model
KERAS_WRAPPER | KERAS_WRAPPER class environment
keras_wrapper | KERAS_WRAPPER class environment
KERAS_WRAPPER$..init.. | Initialization method
KERAS_WRAPPER$..str.. | String representation of the object
KERAS_WRAPPER$get_input_height | Get keras model input image height
KERAS_WRAPPER$get_input_width | Get keras model input image width
KERAS_WRAPPER$image_to_array | Load an image as numpy array
KERAS_WRAPPER$list_layer_name | List all layer names
KERAS_WRAPPER$predict | Predict visual signal strength
list_keras_model | List all available pre-trained computer vision models
remove_plot | Remove a plot
residual_checker | AUTO_VI class environment
save_plot | Save plot(s)