% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/sparcc_matrix_rcpp.R
\name{sparcc_pvalue_rcpp}
\alias{sparcc_pvalue_rcpp}
\title{SparCC p-value matrix (Rcpp implementation)}
\usage{
sparcc_pvalue_rcpp(
  data,
  iter = 20,
  inner_iter = 10,
  th = 0.1,
  R = 20,
  ncpus = 1
)
}
\arguments{
\item{data}{Numeric matrix. Rows = samples, columns = taxa (ASVs/OTUs).}

\item{iter}{Integer. Number of outer iterations (Dirichlet resampling).
Default 20.}

\item{inner_iter}{Integer. Max inner iterations for pair exclusion.
Default 10.}

\item{th}{Numeric. Threshold for excluding highly correlated pairs.
Default 0.1.}

\item{R}{Integer. Number of bootstrap/permutation replicates. Default 20.}

\item{ncpus}{Integer. Number of CPUs for parallel boot. Default 1.}
}
\value{
Numeric matrix of taxa x taxa p-values. Diagonal = 0.
  NaN indicates observed correlation outside bootstrap CI.
}
\description{
Fast C++-accelerated SparCC p-values via bootstrap and permutation.
Uses \code{sparcc_matrix_rcpp} internally for speed. Input: samples x taxa matrix.
Output: taxa x taxa p-value matrix.
}
\examples{
\dontrun{
p_mat <- sparcc_pvalue_rcpp(asv_mat, R = 20, ncpus = 4)
}
}
