gallery.yml

- category: Linear regression models
  description: ""
  tiles:
    - title: Comparison of two means
      subtitle: With a t-test
      href: t-test.ipynb
      thumbnail: thumbnails/t_test.png
    - title: Multiple linear regression
      subtitle: Personality dimensions
      href: ESCS_multiple_regression.ipynb
      thumbnail: thumbnails/escs_multiple_regression.png
    - title: Regression splines
      subtitle: Cherry blossoms
      href: splines_cherry_blossoms.ipynb
      thumbnail: thumbnails/splines_cherry_blossoms.png
    - title: Hierarchical linear regression
      subtitle: Pigs growth
      href: multi-level_regression.ipynb
      thumbnail: thumbnails/multi_level_regression.png
    - title: Hierarchical linear regression
      subtitle: Sleep deprivation
      href: sleepstudy.ipynb
      thumbnail: thumbnails/sleepstudy.png
    - title: Hierarchical linear regression
      subtitle: Radon contamination
      href: radon_example.ipynb
      thumbnail: thumbnails/radon_example.png
    - title: Bayesian workflow
      subtitle: Strack RRR analysis replication
      href: Strack_RRR_re_analysis.ipynb
      thumbnail: thumbnails/strack_rrr_re_analysis.png
    - title: Bayesian workflow
      subtitle: Police officer's dilemma
      href: shooter_crossed_random_ANOVA.ipynb
      thumbnail: thumbnails/shooter_crossed_random_anova.png
    - title: Robust linear regression
      subtitle: With the Student's T distribution
      href: t_regression.ipynb
      thumbnail: thumbnails/t_regression.png
    - title: Predict new groups
      subtitle: With Hierarchical models
      href: predict_new_groups.ipynb
      thumbnail: thumbnails/predict_new_group.png
    - title: Polynomial regression
      subtitle: Learning gravity with Bayesian stats
      href: polynomial_regression.ipynb
      thumbnail: thumbnails/polynomial_regression.png
- category: Generalized Linear Models
  description: ""
  tiles:
    - title: Logistic regression
      subtitle: Model vote intention
      href: logistic_regression.ipynb
      thumbnail: thumbnails/logistic_regression.png
    - title: Logistic regression 
      subtitle: Model comparison with ArviZ
      href: model_comparison.ipynb
      thumbnail: thumbnails/model_comparison.png
    - title: Hierarchical logistic regression 
      subtitle: With the Binomial family
      href: hierarchical_binomial_bambi.ipynb
      thumbnail: thumbnails/hierarchical_binomial_bambi.png
    - title: Regression for binary responses
      subtitle: Alternative link functions
      href: alternative_links_binary.ipynb
      thumbnail: thumbnails/alternative_links_binary.png
    - title: Wald and Gamma regression
      subtitle: Australian insurance claims
      href: wald_gamma_glm.ipynb
      thumbnail: thumbnails/wald_gamma_glm.png
    - title: Negative Binomial regression
      subtitle: Students absence
      href: negative_binomial.ipynb
      thumbnail: thumbnails/negative_binomial.png
    - title: Count Regression with Variable Exposure
      subtitle: Accounting for varying exposure using offsets
      href: count_roaches.ipynb
      thumbnail: thumbnails/roaches.png
    - title: Beta regression
      subtitle: With many datasets
      href: beta_regression.ipynb
      thumbnail: thumbnails/beta_regression.png
    - title: Categorical outcomes
      subtitle: When the outcome is not a number
      href: categorical_regression.ipynb
      thumbnail: thumbnails/categorical_regression.png
    - title: Circular regression
      subtitle: For directional statistics
      href: circular_regression.ipynb
      thumbnail: thumbnails/circular_regression.png
    - title: Quantile regression
      subtitle: Model a percentile
      href: quantile_regression.ipynb
      thumbnail: thumbnails/quantile_regression.png
    - title: MrP (Multilevel Regression and Post-stratification)
      subtitle: Survey Data and Representative Sampling
      href: mister_p.ipynb
      thumbnail: thumbnails/mr_p_adjustment.png
    - title: Zero inflated models
      subtitle: When the outcome is mostly zeros and or is overdispersed
      href: zero_inflated_regression.ipynb
      thumbnail: thumbnails/zip_model_pps.png
    - title: Ordinal regression
      subtitle: Model ordered category outcomes
      href: ordinal_regression.ipynb
      thumbnail: thumbnails/ordinal_regression.png
- category: More advanced models
  description: ""
  tiles:
    - title: Distributional models
      subtitle: Many parameters simultaneously
      href: distributional_models.ipynb
      thumbnail: thumbnails/distributional_models.png
    - title: Gaussian processes
      subtitle: In one dimension
      href: hsgp_1d.ipynb
      thumbnail: thumbnails/hsgp_1d.png
    - title: Gaussian processes
      subtitle: In multiple dimensions
      href: hsgp_2d.ipynb
      thumbnail: thumbnails/hsgp_2d.png
    - title: Survival models
      subtitle: Model censored data
      href: survival_model.ipynb
      thumbnail: thumbnails/survival_adoption_times.png
    - title: Orthogonal Polynomial regression
      subtitle: Polynomials that avoid multicollinearity
      href: orthogonal_polynomial_reg.ipynb
      thumbnail: thumbnails/orthogonal_polynomial_reg.png
- category: Tools to interpret model outputs
  description: ""
  tiles:
    - title: Predictions
      subtitle: Compute and plot predictions on new data
      href: plot_predictions.ipynb
      thumbnail: thumbnails/plot_predictions.png
    - title: Comparisons
      subtitle: Compare outputs between groups
      href: plot_comparisons.ipynb
      thumbnail: thumbnails/plot_comparisons.png
    - title: Slopes
      subtitle: Determine how the response changes 
      href: plot_slopes.ipynb
      thumbnail: thumbnails/plot_slopes.png
    - title: Advanced interpret usage
      subtitle: Create data grids and compute complex quantities of interest
      href: interpret_advanced_usage.ipynb
      thumbnail: thumbnails/advanced_interpret.png
- category: Alternative sampling backends
  description: ""
  tiles:
    - title: Using other samplers
      subtitle: JAX based samplers
      href: alternative_samplers.ipynb