# Resampling Strategies

> Resampling strategies in tidymodels, including validation splits, cross-validation, bootstrap, nested resampling, and grouped data.

- **Type:** Skill
- **Install:** `agentstack add skill-choxos-biostatagent-resampling-strategies`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [choxos](https://agentstack.voostack.com/s/choxos)
- **Installs:** 0
- **Category:** [Agent Skills](https://agentstack.voostack.com/c/agent-skills)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [choxos](https://github.com/choxos)
- **Source:** https://github.com/choxos/BiostatAgent/tree/main/plugins/r-tidy-modeling/skills/resampling-strategies

## Install

```sh
agentstack add skill-choxos-biostatagent-resampling-strategies
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# Resampling Strategies

## Overview

Comprehensive guide to resampling methods for model validation using the rsample package. Covers cross-validation, bootstrapping, and specialized resampling for time series and grouped data.

## Data Splitting

### Basic Train/Test Split

```r
library(rsample)

set.seed(123)

# Simple split (75% training)
split 
  mutate(
    model = map(splits, ~ lm(y ~ x, data = analysis(.x))),
    coefs = map(model, tidy)
  ) |>
  unnest(coefs)

# Calculate confidence intervals
boot_ci 
  tune_grid(
    resamples = outer_folds,  # outer loop
    grid = 20
  )
```

## Time Series Resampling

### Rolling Origin

```r
# Time series cross-validation
ts_folds 
  fit_resamples(
    resamples = folds,
    metrics = metric_set(rmse, rsq, mae),
    control = control_resamples(save_pred = TRUE)
  )

# Collect metrics
collect_metrics(results)

# Collect predictions
collect_predictions(results)
```

### Custom Resampling

```r
# Create custom resample object
custom_splits  10000)
folds 
  tune_grid(
    resamples = vfold_cv(train, v = 10, strata = outcome),
    grid = 20,
    metrics = metric_set(roc_auc, accuracy)
  )

# Tune with bootstrap
tune_results 
  tune_bayes(
    resamples = bootstraps(train, times = 25),
    iter = 50
  )
```

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [choxos](https://github.com/choxos)
- **Source:** [choxos/BiostatAgent](https://github.com/choxos/BiostatAgent)
- **License:** MIT

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-choxos-biostatagent-resampling-strategies
- Seller: https://agentstack.voostack.com/s/choxos
- Browse the marketplace: https://agentstack.voostack.com/browse

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