{
  "_id": "6a185b3aacfb0bcc41dbb548",
  "Package": "MixtureFitting",
  "Version": "0.8.0",
  "Date": "2026-05-18",
  "Title": "Fitting of Univariate Mixture Distributions to Data using\nVarious Approaches",
  "Authors@R": "person(given = \"Andrius\",\nfamily = \"Merkys\",\nrole = c(\"aut\", \"cre\"),\nemail = \"andrius.merkys@gmail.com\")",
  "Description": "Methods for fitting mixture distributions to univariate\ndata using expectation maximization, HWHM and other methods.\nSupports Gaussian, Cauchy, Student's t, skew-normal and von\nMises mixtures. For more details see Merkys (2018)\n<https://www.lvb.lt/permalink/370LABT_NETWORK/1m6ui06/alma9910036312108451>.",
  "License": "GPL-2",
  "Repository": "https://merkys.r-universe.dev",
  "Date/Publication": "2026-05-27 10:27:53 UTC",
  "RemoteUrl": "https://github.com/merkys/mixturefitting",
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  "NeedsCompilation": "yes",
  "Packaged": {
    "Date": "2026-05-28 14:48:05 UTC",
    "User": "root"
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  "Author": "Andrius Merkys [aut, cre]",
  "Maintainer": "Andrius Merkys <andrius.merkys@gmail.com>",
  "MD5sum": "2449130fcb02a5881181e77b6ae32502",
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    "message": "Fix NaN detection in snmm_fit_em().\n",
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      "date": "2026-04-23"
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    "mixture-modelling",
    "statistics"
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  "_contributors": [
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    "extra/citation.json",
    "extra/citation.txt",
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    "extra/MixtureFitting.html",
    "manual.pdf"
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  "_homeurl": "https://github.com/merkys/mixturefitting",
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      "date": "2025-05-27"
    },
    {
      "version": "0.8.0",
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  "_exports": [
    "abs_convergence",
    "aic",
    "bhattacharyya_dist",
    "bic",
    "cmm_fit_em",
    "cmm_fit_hwhm_spline_deriv",
    "cmm_init_vector",
    "cmm_init_vector_kmeans",
    "cmm_intersections",
    "dcmm",
    "dgmm",
    "digamma_approx",
    "ds",
    "dsmm",
    "dsnmm",
    "dvmm",
    "gmm_fit_em",
    "gmm_fit_hwhm",
    "gmm_fit_hwhm_spline_deriv",
    "gmm_fit_kmeans",
    "gmm_init_vector",
    "gmm_init_vector_kmeans",
    "gmm_init_vector_quantile",
    "gmm_intersections",
    "gmm_merge_components",
    "gmm_size_probability",
    "gmm_size_probability_nls",
    "gradient_descent",
    "kldiv",
    "kmeans_circular",
    "llcmm",
    "llgmm",
    "llgmm_conservative",
    "llgmm_opposite",
    "llsmm",
    "llsnmm",
    "llvmm",
    "llvmm_opposite",
    "mk_fit_images",
    "plot_circular_hist",
    "plot_density",
    "polyroot_NR",
    "pssd",
    "pssd_gradient",
    "ratio_convergence",
    "rcmm",
    "rgmm",
    "rsimplex_start",
    "rvmm",
    "s_fit_primitive",
    "simplex",
    "smm_fit_em",
    "smm_fit_em_APK10",
    "smm_fit_em_CWL04",
    "smm_fit_em_GNL08",
    "smm_init_vector",
    "smm_init_vector_kmeans",
    "smm_split_component",
    "snmm_fit_em",
    "snmm_init_vector",
    "ssd",
    "ssd_gradient",
    "vmm_fit_em",
    "vmm_fit_em_by_diff",
    "vmm_fit_em_by_ll",
    "vmm_init_vector",
    "wmedian"
  ],
  "_help": [
    {
      "page": "abs_convergence",
      "title": "Absolute Convergence Check.",
      "topics": [
        "abs_convergence"
      ]
    },
    {
      "page": "aic",
      "title": "Akaike Information Criterion (AIC)",
      "topics": [
        "aic"
      ]
    },
    {
      "page": "bhattacharyya_dist",
      "title": "Bhattacharyya distance for univariate Gaussian distributions.",
      "topics": [
        "bhattacharyya_dist"
      ]
    },
    {
      "page": "bic",
      "title": "Bayesian Information Criterion (BIC)",
      "topics": [
        "bic"
      ]
    },
    {
      "page": "cmm_fit_em",
      "title": "Estimate Cauchy Mixture parameters using Expectation Maximization.",
      "topics": [
        "cmm_fit_em"
      ]
    },
    {
      "page": "cmm_fit_hwhm_spline_deriv",
      "title": "Estimate Cauchy Mixture Parameters Using Derivatives and Half-Width at Half-Maximum Method.",
      "topics": [
        "cmm_fit_hwhm_spline_deriv"
      ]
    },
    {
      "page": "cmm_init_vector",
      "title": "Estimate Cauchy Mixture parameters using Expectation Maximization.",
      "topics": [
        "cmm_init_vector"
      ]
    },
    {
      "page": "cmm_init_vector_kmeans",
      "title": "Estimate Cauchy Mixture parameters using Expectation Maximization.",
      "topics": [
        "cmm_init_vector_kmeans"
      ]
    },
    {
      "page": "cmm_intersections",
      "title": "Intersections of Two Cauchy Distributions",
      "topics": [
        "cmm_intersections"
      ]
    },
    {
      "page": "dcgmm",
      "title": "Density of The Cauchy-Gaussian Distribution",
      "topics": [
        "dcgmm"
      ]
    },
    {
      "page": "dcmm",
      "title": "Density of The Cauchy Mixture Distribution",
      "topics": [
        "dcmm"
      ]
    },
    {
      "page": "dgmm",
      "title": "The Gaussian Mixture Distribution",
      "topics": [
        "dgmm"
      ]
    },
    {
      "page": "digamma_approx",
      "title": "Calculate Approximate Value of The Digamma Function.",
      "topics": [
        "digamma_approx"
      ]
    },
    {
      "page": "ds",
      "title": "Density of The Student's t Model",
      "topics": [
        "ds"
      ]
    },
    {
      "page": "dsmm",
      "title": "Density of The Student's t Mixture Model",
      "topics": [
        "dsmm"
      ]
    },
    {
      "page": "dsnmm",
      "title": "Density of The Skew-Normal Mixture Model",
      "topics": [
        "dsnmm"
      ]
    },
    {
      "page": "dvmm",
      "title": "Density of The von Mises Mixture Model.",
      "topics": [
        "dvmm"
      ]
    },
    {
      "page": "gmm_fit_em",
      "title": "Estimate Gaussian Mixture parameters using Expectation Maximization.",
      "topics": [
        "gmm_fit_em"
      ]
    },
    {
      "page": "gmm_fit_hwhm",
      "title": "Estimate Gaussian Mixture Parameters Using Half-Width at Half-Maximum Method.",
      "topics": [
        "gmm_fit_hwhm"
      ]
    },
    {
      "page": "gmm_fit_hwhm_spline_deriv",
      "title": "Estimate Gaussian Mixture Parameters Using Derivatives and Half-Width at Half-Maximum Method.",
      "topics": [
        "gmm_fit_hwhm_spline_deriv"
      ]
    },
    {
      "page": "gmm_fit_kmeans",
      "title": "Estimate Gaussian Mixture parameters from kmeans.",
      "topics": [
        "gmm_fit_kmeans"
      ]
    },
    {
      "page": "gmm_init_vector",
      "title": "Estimate Gaussian Mixture parameters using Expectation Maximization.",
      "topics": [
        "gmm_init_vector"
      ]
    },
    {
      "page": "gmm_init_vector_kmeans",
      "title": "Estimate Gaussian Mixture parameters using Expectation Maximization.",
      "topics": [
        "gmm_init_vector_kmeans"
      ]
    },
    {
      "page": "gmm_init_vector_quantile",
      "title": "Estimate Gaussian Mixture parameters using Expectation Maximization.",
      "topics": [
        "gmm_init_vector_quantile"
      ]
    },
    {
      "page": "gmm_intersections",
      "title": "Intersections of Two Gaussian Distributions",
      "topics": [
        "gmm_intersections"
      ]
    },
    {
      "page": "gmm_merge_components",
      "title": "Merge two Gaussian components into one.",
      "topics": [
        "gmm_merge_components"
      ]
    },
    {
      "page": "gmm_size_probability",
      "title": "The Gaussian Mixture Distribution",
      "topics": [
        "gmm_size_probability"
      ]
    },
    {
      "page": "gmm_size_probability_nls",
      "title": "The Gaussian Mixture Distribution",
      "topics": [
        "gmm_size_probability_nls"
      ]
    },
    {
      "page": "gradient_descent",
      "title": "Gradient Descent",
      "topics": [
        "gradient_descent"
      ]
    },
    {
      "page": "kldiv",
      "title": "Kullback-Leibler Divergence of _i_th Student's t Mixture component.",
      "topics": [
        "kldiv"
      ]
    },
    {
      "page": "kmeans_circular",
      "title": "K-Means Clustering for Points on Circle",
      "topics": [
        "kmeans_circular"
      ]
    },
    {
      "page": "llcmm",
      "title": "Log-likelihood for Cauchy Mixture",
      "topics": [
        "llcmm"
      ]
    },
    {
      "page": "llgmm",
      "title": "Log-likelihood for Gaussian Mixture",
      "topics": [
        "llgmm"
      ]
    },
    {
      "page": "llgmm_conservative",
      "title": "Log-likelihood for Gaussian Mixture",
      "topics": [
        "llgmm_conservative"
      ]
    },
    {
      "page": "llgmm_opposite",
      "title": "Opposite Log-likelihood for Gaussian Mixture",
      "topics": [
        "llgmm_opposite"
      ]
    },
    {
      "page": "llsmm",
      "title": "Log-likelihood for Student's t Mixture",
      "topics": [
        "llsmm"
      ]
    },
    {
      "page": "llsnmm",
      "title": "Log-likelihood for Skew-Normal Mixture",
      "topics": [
        "llsnmm"
      ]
    },
    {
      "page": "llvmm",
      "title": "Log-likelihood for von Mises Mixture",
      "topics": [
        "llvmm"
      ]
    },
    {
      "page": "llvmm_opposite",
      "title": "Opposite Log-likelihood for von Mises Mixture",
      "topics": [
        "llvmm_opposite"
      ]
    },
    {
      "page": "mk_fit_images",
      "title": "Mixture Distribution Modeling",
      "topics": [
        "mk_fit_images"
      ]
    },
    {
      "page": "plot_circular_hist",
      "title": "Mixture Distribution Modeling",
      "topics": [
        "plot_circular_hist"
      ]
    },
    {
      "page": "plot_density",
      "title": "Mixture Distribution Modeling",
      "topics": [
        "plot_density"
      ]
    },
    {
      "page": "polyroot_NR",
      "title": "Find one real polynomial root using Newton-Raphson method.",
      "topics": [
        "polyroot_NR"
      ]
    },
    {
      "page": "pssd",
      "title": "Penalized Sum of Squared Differences Using Gaussian Mixture Distribution",
      "topics": [
        "pssd"
      ]
    },
    {
      "page": "pssd_gradient",
      "title": "Penalized Sum of Squared Differences Using Gaussian Mixture Distribution",
      "topics": [
        "pssd_gradient"
      ]
    },
    {
      "page": "ratio_convergence",
      "title": "Ratio Convergence Check.",
      "topics": [
        "ratio_convergence"
      ]
    },
    {
      "page": "rcmm",
      "title": "Random Sample of The Cauchy Mixture Distribution",
      "topics": [
        "rcmm"
      ]
    },
    {
      "page": "rgmm",
      "title": "Random Sample of the Gaussian Mixture Distribution",
      "topics": [
        "rgmm"
      ]
    },
    {
      "page": "rsimplex_start",
      "title": "Nelder-Mead's Simplex Method for Function Minimization.",
      "topics": [
        "rsimplex_start"
      ]
    },
    {
      "page": "rvmm",
      "title": "Random Sample of the von Mises Mixture Model.",
      "topics": [
        "rvmm"
      ]
    },
    {
      "page": "s_fit_primitive",
      "title": "Estimate Student's t distribution parameters using Batch Approximation Algorithm.",
      "topics": [
        "s_fit_primitive"
      ]
    },
    {
      "page": "simplex",
      "title": "Nelder-Mead's Simplex Method for Function Minimization.",
      "topics": [
        "simplex"
      ]
    },
    {
      "page": "smm_fit_em",
      "title": "Estimate Student's t Mixture parameters using Expectation Maximization.",
      "topics": [
        "smm_fit_em"
      ]
    },
    {
      "page": "smm_fit_em_APK10",
      "title": "Estimate Student's t Mixture parameters using Expectation Maximization.",
      "topics": [
        "smm_fit_em_APK10"
      ]
    },
    {
      "page": "smm_fit_em_CWL04",
      "title": "Greedily estimate Student's t Mixture parameters using Expectation Maximization.",
      "topics": [
        "smm_fit_em_CWL04"
      ]
    },
    {
      "page": "smm_fit_em_GNL08",
      "title": "Estimate Student's t Mixture parameters using Expectation Maximization.",
      "topics": [
        "smm_fit_em_GNL08"
      ]
    },
    {
      "page": "smm_init_vector",
      "title": "Estimate Student's t Mixture parameters using Expectation Maximization.",
      "topics": [
        "smm_init_vector"
      ]
    },
    {
      "page": "smm_init_vector_kmeans",
      "title": "Estimate Student's t Mixture parameters using Expectation Maximization.",
      "topics": [
        "smm_init_vector_kmeans"
      ]
    },
    {
      "page": "smm_split_component",
      "title": "Split a component of Student's t-distribution in two.",
      "topics": [
        "smm_split_component"
      ]
    },
    {
      "page": "snmm_fit_em",
      "title": "Estimate Skew-Normal Mixture parameters using Expectation Maximization.",
      "topics": [
        "snmm_fit_em"
      ]
    },
    {
      "page": "snmm_init_vector",
      "title": "Estimate Skew-Normal Mixture parameters using Expectation Maximization.",
      "topics": [
        "snmm_init_vector"
      ]
    },
    {
      "page": "ssd",
      "title": "Sum of Squared Differences Using Gaussian Mixture Distribution",
      "topics": [
        "ssd"
      ]
    },
    {
      "page": "ssd_gradient",
      "title": "Sum of Squared Differences Using Gaussian Mixture Distribution",
      "topics": [
        "ssd_gradient"
      ]
    },
    {
      "page": "vmm_fit_em",
      "title": "Estimate von Mises Mixture parameters using Expectation Maximization.",
      "topics": [
        "vmm_fit_em"
      ]
    },
    {
      "page": "vmm_fit_em_by_diff",
      "title": "Estimate von Mises Mixture parameters using Expectation Maximization.",
      "topics": [
        "vmm_fit_em_by_diff"
      ]
    },
    {
      "page": "vmm_fit_em_by_ll",
      "title": "Estimate von Mises Mixture parameters using Expectation Maximization.",
      "topics": [
        "vmm_fit_em_by_ll"
      ]
    },
    {
      "page": "vmm_init_vector",
      "title": "Estimate von Mises Mixture parameters using Expectation Maximization.",
      "topics": [
        "vmm_init_vector"
      ]
    },
    {
      "page": "wmedian",
      "title": "Calculate Weighted Median.",
      "topics": [
        "wmedian"
      ]
    }
  ],
  "_rundeps": [
    "lattice",
    "MASS",
    "Matrix",
    "MatrixModels",
    "mnormt",
    "numDeriv",
    "quantreg",
    "sn",
    "SparseM",
    "survival"
  ],
  "_score": 2.6989700043360187,
  "_indexed": true,
  "_nocasepkg": "mixturefitting",
  "_universes": [
    "merkys"
  ],
  "_binaries": [
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      "date": "2026-05-28T14:50:18.000Z",
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      "arch": "aarch64",
      "commit": "8d9a616a17d5ae61e0717ada85c8b37efaea84c8",
      "fileid": "4bbad3dc185cb459236527abc51de4161a2f7bbf57378406a2c2965da20973e7",
      "status": "success",
      "check": "OK",
      "buildurl": "https://github.com/r-universe/merkys/actions/runs/26581811515"
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