GET /api/v1/autocomplete/port/?format=api&page=711
HTTP 200 OK
Allow: GET, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept

{
    "count": 42450,
    "next": "https://ports.macports.org/api/v1/autocomplete/port/?format=api&page=712",
    "previous": "https://ports.macports.org/api/v1/autocomplete/port/?format=api&page=710",
    "results": [
        {
            "name": "R-lctools",
            "description": "Local correlation, spatial inequalities, geographically-weighted regression and other tools"
        },
        {
            "name": "R-lda",
            "description": "Collapsed Gibbs sampling methods for topic models"
        },
        {
            "name": "R-LDAvis",
            "description": "Interactive visualization of topic models"
        },
        {
            "name": "R-ldbod",
            "description": "Local density-based outlier detection"
        },
        {
            "name": "R-ldbounds",
            "description": "Lan–DeMets method for group sequential boundaries"
        },
        {
            "name": "R-lddmm",
            "description": "Longitudinal Drift-Diffusion Mixed Models (LDDMM)"
        },
        {
            "name": "R-ldt",
            "description": "Automated model sensitivity analysis"
        },
        {
            "name": "R-leaflet",
            "description": "Create and customize interactive maps"
        },
        {
            "name": "R-leaflet.providers",
            "description": "Leaflet providers"
        },
        {
            "name": "R-leaps",
            "description": "Regression subset selection"
        },
        {
            "name": "R-LearnBayes",
            "description": "Functions for learning Bayesian inference"
        },
        {
            "name": "R-lefko3",
            "description": "Historical and ahistorical population projection matrix analysis"
        },
        {
            "name": "R-legion",
            "description": "Forecasting using multivariate models"
        },
        {
            "name": "R-leiden",
            "description": "R implementation of Leiden clustering algorithm"
        },
        {
            "name": "R-leidenAlg",
            "description": "R interface to the Leiden algorithm, an iterative community detection algorithm on networks"
        },
        {
            "name": "R-leidenbase",
            "description": "R and C/C++ wrappers to run the Leiden find_partition() function"
        },
        {
            "name": "R-lemon",
            "description": "Freshing up your ggplot2 plots"
        },
        {
            "name": "R-leptokurticMixture",
            "description": "Parsimonious finite mixtures of multivariate elliptical leptokurtic-normals"
        },
        {
            "name": "R-lessSEM",
            "description": "Non-smooth regularization for structural equation models"
        },
        {
            "name": "R-lestat",
            "description": "Some simple objects and functions to do statistics using linear models and a Bayesian framework"
        },
        {
            "name": "R-levmaR",
            "description": "Interface for the Levenberg–Marquardt optimization algorithm provided by the levmar Library"
        },
        {
            "name": "R-lfda",
            "description": "Local Fisher Discriminant Analysis"
        },
        {
            "name": "R-lfe",
            "description": "Linear Group Fixed Effects"
        },
        {
            "name": "R-lfmm",
            "description": "Latent Factor Mixed Models"
        },
        {
            "name": "R-lg",
            "description": "Locally Gaussian distributions – estimation and methods"
        },
        {
            "name": "R-lgarch",
            "description": "Simulation and estimation of Log-GARCH models"
        },
        {
            "name": "R-lgpr",
            "description": "Longitudinal Gaussian Process Regression"
        },
        {
            "name": "R-lgr",
            "description": "Fully featured logging framework"
        },
        {
            "name": "R-lhs",
            "description": "Latin Hypercube Samples"
        },
        {
            "name": "R-libbib",
            "description": "Various utilities for library science/assessment and cataloging"
        },
        {
            "name": "R-libcoin",
            "description": "Linear test statistics for permutation inference"
        },
        {
            "name": "R-libgeos",
            "description": "Open Source Geometry Engine (GEOS) C API"
        },
        {
            "name": "R-LiblineaR",
            "description": "Linear predictive models based on the liblinear C/C++ library"
        },
        {
            "name": "R-libr",
            "description": "Libraries, data dictionaries and a data step for R"
        },
        {
            "name": "R-libstable4u",
            "description": "Tools for fast and accurate evaluation of skew stable distributions"
        },
        {
            "name": "R-libstableR",
            "description": "Fast and accurate evaluation, random number generation and parameter estimation of skew stable distributions"
        },
        {
            "name": "R-LIC",
            "description": "LIC Criterion for Optimal Subset Selection"
        },
        {
            "name": "R-lifecycle",
            "description": "Manage the life cycle of your exported functions and arguments"
        },
        {
            "name": "R-lightgbm",
            "description": "Light Gradient Boosting Machine"
        },
        {
            "name": "R-lightparser",
            "description": "From Rmarkdown and R-quarto files to R-tibble and back"
        },
        {
            "name": "R-likelihood",
            "description": "Methods for maximum likelihood estimation"
        },
        {
            "name": "R-likelihoodR",
            "description": "Likelihood analyses for common statistical tests"
        },
        {
            "name": "R-likert",
            "description": "Approach to analyzing Likert response items, with an emphasis on visualizations"
        },
        {
            "name": "R-lime",
            "description": "Local Interpretable Model-Agnostic Explanations"
        },
        {
            "name": "R-limma",
            "description": "Linear models for microarray data"
        },
        {
            "name": "R-limSolve",
            "description": "Solving linear inverse models"
        },
        {
            "name": "R-lin.eval",
            "description": "Polynomial evaluation of linearity"
        },
        {
            "name": "R-linprog",
            "description": "Linear Programming/Optimization"
        },
        {
            "name": "R-LINselect",
            "description": "Selection of linear estimators"
        },
        {
            "name": "R-lintools",
            "description": "Manipulation of linear systems of (in)equalities"
        }
    ]
}