Function parallel_normal_sample 

pub fn parallel_normal_sample(
    n: usize,
    mean: f64,
    std_dev: f64,
    seed: Option<u64>,
) -> StatsResult<Vec<f64>>

Generate n independent samples from N(mean, std_dev²) using parallel threads (via Rayon) and per-thread SIMD Box-Muller kernels.

The work is split into num_cpus chunks. Each chunk receives a deterministic seed derived from the user-supplied seed and the chunk index, making the output fully reproducible when seed is provided.

Arguments

• n — Total number of samples to generate.
• mean — Location parameter of the Normal distribution.
• std_dev — Scale parameter (must be positive).
• seed — Optional base RNG seed for reproducibility.

Errors

Returns StatsError::InvalidArgument when n == 0 or std_dev <= 0.

Examples

use scirs2_stats::simd_sampling::parallel_normal_sample;

let samples = parallel_normal_sample(10_000, 5.0_f64, 2.0_f64, Some(42))
    .expect("parallel sampling failed");
assert_eq!(samples.len(), 10_000);
let mean: f64 = samples.iter().sum::<f64>() / 10_000.0;
assert!((mean - 5.0).abs() < 0.2, "empirical mean {mean} too far from 5.0");