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implemrnts the composite quantile correlation-sure independence screening (CQC-SIS).\npackage\n\n\n\n\n\n```r\nCQCSIS(x, y, d)\n```\n\n## Arguments\n\n- `x`: The design matrix, of dimensions n * p, without an intercept.\n- `y`: The response vector of dimension n * 1.\n- `d`: The tuning parameter used to covarites had significant effect on the response variable, such as [n/log(n)], or n-1.\n\n## Returns\n\n- **w**: The estimate of w.\n\n- **M**: The subscript of x recuited by CQC-SIS.\n\n## Author(s)\n\ntools:::Rd_package_author(\"QCSIS\")\n\n## References\n\nXuejun Ma et al.. Robust feature screening via composite quantile correlation learning. In submission.\n\n## Examples\n\n```r\nn <- 20\np <- 200\nx <- matrix(rnorm(n * p), n, p)\ne <- rnorm(n, 0, 1)\nbeta1 <- 3 - runif(1)\nbeta2 <- 3 - runif(1)\nbeta3 <- 3 - runif(1)\ny <- beta1 * x[, 1] + beta2 * x[, 2] + beta3 * x[, 3] + e\nd <- 19\nfit.CQCSIS <- CQCSIS(x = x, y = y, d = d)\nfit.CQCSIS$M\n```"}]}]}]}]}]}],["$","div",null,{"className":"lg:w-1/3 lg:border-l px-1 sm:px-8 pt-8 sm:pt-1","children":[["$","div",null,{"className":"mb-8 space-y-8","children":[["$","a",null,{"href":"/packages/QCSIS","className":"w-full inline-flex items-center justify-center p-4 text-base font-medium text-gray-600 rounded-lg bg-muted hover:text-gray-900 hover:bg-gray-100 dark:text-gray-400 dark:bg-gray-800 dark:hover:bg-gray-700 dark:hover:text-white","children":[["$","svg",null,{"xmlns":"http://www.w3.org/2000/svg","width":24,"height":24,"viewBox":"0 0 24 24","fill":"none","stroke":"currentColor","strokeWidth":2,"strokeLinecap":"round","strokeLinejoin":"round","className":"lucide lucide-package 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