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            "name": "R-JointFPM",
            "description": "Parametric model for estimating the mean number of events"
        },
        {
            "name": "R-jointPm",
            "description": "Risk estimation using the joint probability method"
        },
        {
            "name": "R-jointseg",
            "description": "Joint segmentation of multivariate (copy number) signals"
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        {
            "name": "R-jomo",
            "description": "Multi-level joint modelling multiple imputation"
        },
        {
            "name": "R-jordan",
            "description": "Suite of routines for working with Jordan algebras"
        },
        {
            "name": "R-jose",
            "description": "JavaScript Object Signing and Encryption"
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        {
            "name": "R-jpeg",
            "description": "Read and write JPEG images"
        },
        {
            "name": "R-jqr",
            "description": "Client for jq, a JSON processor"
        },
        {
            "name": "R-jquerylib",
            "description": "Obtain jQuery as an HTML dependency object"
        },
        {
            "name": "R-js",
            "description": "Tools for working with JavaScript in R"
        },
        {
            "name": "R-json64",
            "description": "Base64 encode/decode package with support for JSON output/input and UTF-8"
        },
        {
            "name": "R-jsonify",
            "description": "Convert between R objects and JavaScript Object Notation (JSON)"
        },
        {
            "name": "R-jsonlite",
            "description": "Robust, high-performance JSON parser and generator"
        },
        {
            "name": "R-jsontools",
            "description": "Working with JSON vectors"
        },
        {
            "name": "R-jstable",
            "description": "Create tables from different types of regression"
        },
        {
            "name": "R-jstor",
            "description": "Functions and helpers to import metadata, ngrams and full-texts delivered by Data for Research by JSTOR"
        },
        {
            "name": "R-jsTreeR",
            "description": "Wrapper of the JavaScript library jsTree"
        },
        {
            "name": "R-jtools",
            "description": "Analysis and presentation of social scientific data"
        },
        {
            "name": "R-JuliaCall",
            "description": "Seamless integration between R and Julia"
        },
        {
            "name": "R-JuliaConnectoR",
            "description": "Functionally-oriented interface for integrating Julia with R"
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        {
            "name": "R-kableExtra",
            "description": "Construct complex table with kable and pipe syntax"
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        {
            "name": "R-kader",
            "description": "Kernel adaptive density estimation and regression"
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            "name": "R-kalmanfilter",
            "description": "Kalman Filter"
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        {
            "name": "R-kangar00",
            "description": "Kernel approaches for non-linear genetic association regression"
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        {
            "name": "R-kanjistat",
            "description": "Statistical framework for the analysis of Japanese Kanji characters"
        },
        {
            "name": "R-kantorovich",
            "description": "Kantorovich distance between probability measures"
        },
        {
            "name": "R-kappalab",
            "description": "Non-additive measure and integral manipulation functions"
        },
        {
            "name": "R-kazaam",
            "description": "Tools for tall distributed matrices"
        },
        {
            "name": "R-KbMvtSkew",
            "description": "Compute Khattree–Bahuguna’s univariate and multivariate skewness"
        },
        {
            "name": "R-kcmeans",
            "description": "Conditional expectation function estimation with k-conditional-means"
        },
        {
            "name": "R-kcopula",
            "description": "Bivariate k-copula"
        },
        {
            "name": "R-kcpRS",
            "description": "Kernel change point detection on the running statistics"
        },
        {
            "name": "R-kde1d",
            "description": "Univariate kernel density estimation"
        },
        {
            "name": "R-kdecopula",
            "description": "Kernel smoothing for bivariate copula densities"
        },
        {
            "name": "R-kdensity",
            "description": "Kernel density estimation with parametric starts and asymmetric kernels"
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        {
            "name": "R-kDGLM",
            "description": "Bayesian analysis of Dynamic Generalized Linear Models"
        },
        {
            "name": "R-kdist",
            "description": "K-distribution and Weibull paper"
        },
        {
            "name": "R-kebabs",
            "description": "Kernel-Based Analysis of Biological Sequences"
        },
        {
            "name": "R-keep",
            "description": "Arrays with better control over dimension dropping"
        },
        {
            "name": "R-KEGGgraph",
            "description": "A graph approach to KEGG pathway in R and Bioconductor"
        },
        {
            "name": "R-KEGGREST",
            "description": "Client-side REST access to the Kyoto Encyclopedia of Genes and Genomes (KEGG)"
        },
        {
            "name": "R-Kendall",
            "description": "Kendall Rank Correlation and Mann–Kendall Trend Test"
        },
        {
            "name": "R-kerDAA",
            "description": "New kernel-based test for differential association analysis"
        },
        {
            "name": "R-KERE",
            "description": "Expectile regression in reproducing kernel Hilbert space"
        },
        {
            "name": "R-kernelboot",
            "description": "Smoothed bootstrap and random generation from kernel densities"
        },
        {
            "name": "R-KernelKnn",
            "description": "Kernel k-nearest neighbors"
        },
        {
            "name": "R-kernelshap",
            "description": "Kernel SHAP"
        },
        {
            "name": "R-kernhaz",
            "description": "Kernel estimation of hazard function in survival analysis"
        },
        {
            "name": "R-kernlab",
            "description": "Kernel-based machine learning lab"
        },
        {
            "name": "R-KernSmooth",
            "description": "Functions for kernel smoothing (and density estimation)"
        }
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}