Add CRAN-compliant example to set_hyperparameters documentation

[Copilot]

The set_hyperparameters function lacked documentation examples and had minimal parameter descriptions, making it difficult for users to understand how to configure priors for the Bayesian Mallows model.

Changes

• Enhanced parameter documentation: Expanded descriptions for alpha_shape, alpha_rate, and cluster_concentration to clarify their statistical meaning and when they're used
• Improved return value: Documented all list components returned by the function
• Added runnable example: Demonstrates setting custom hyperparameters and using them with compute_sequentially on the partial_rankings dataset
• CRAN-optimized parameters: Example uses 20 particles and 4 particle filters for fast execution during package checks

Example

# Set custom prior for alpha parameter
hyperparams <- set_hyperparameters(
  n_items = 5, 
  alpha_shape = 2,  # Higher shape increases prior mean
  alpha_rate = 1
)

# Use with compute_sequentially
mod <- compute_sequentially(
  partial_rankings,
  hyperparameters = hyperparams,
  smc_options = set_smc_options(
    n_particles = 20, 
    n_particle_filters = 4
  )
)

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Original prompt

---

This section details on the original issue you should resolve

<issue_title>Document set_hyperparameters</issue_title>
<issue_description>Update the documentation to set_hyperparameters so that it is CRAN compliant. Create an example using the included partial_rankings dataset which also shows how compute_sequentially can be used with different hyperparameters. Make it simple and short so that it runs in the time required on CRAN. For example 20 particles and 4 particle filters would be fine.</issue_description>

<agent_instructions>Make sure the example runs</agent_instructions>

Comments on the Issue (you are @copilot in this section)

• Fixes Document set_hyperparameters #49

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