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replicate-specific cepstral coefficients and corresponding smoothed log-spectra using a Whittle likelihood approximation.\n\n\n```r\nspec_regress(perd, psi, Wmat, k0)\n```\n\n## Arguments\n\n- `perd`: An N x K matrix of periodogram.\n- `psi`: A matrix of cepstral basis functions of dimension `k0 × K`.\n- `Wmat`: The inverse Gram matrix of the basis functions.\n- `k0`: Number of cepstral basis function\n\n## Returns\n\nA list with:\n\n- **`f`**: An `N × k0` matrix of estimated cepstral coefficients.\n- **`ff`**: An `N × K` matrix of smoothed log-spectra.\n\n\n\n## Examples\n\n```r\nset.seed(123)\nN <- 5\nlen <- 20\nL <- floor(len/2) - 1\nfrq <- (1:L) / len\n\nY <- matrix(rnorm(len * N), nrow = len, ncol = N)\n\nperd <- perd_get(Y)\n\nk0 <- 3\npsi <- psi_get(k0, frq)\n\nWmatin <- matrix(0, k0, k0)\nfor (j in 1:ncol(psi)) {\n Wmatin <- Wmatin + psi[, j] %*% t(psi[, j])\n}\nWmat <- solve(Wmatin)\n\nout <- spec_regress(perd, psi, Wmat, 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