{"count":42452,"next":"https://ports.macports.org/api/v1/autocomplete/port/?format=json&page=709","previous":"https://ports.macports.org/api/v1/autocomplete/port/?format=json&page=707","results":[{"name":"R-JM","description":"Joint modelling of longitudinal and survival data"},{"name":"R-jmatrix","description":"Read from/write to disk matrices with any data type in a binary format"},{"name":"R-JMbayes","description":"Joint modelling of longitudinal and time-to-event data under a Bayesian approach"},{"name":"R-JMbayes2","description":"Network meta-analysis using Bayesian methods"},{"name":"R-JMdesign","description":"Power calculations for joint modelling of longitudinal and survival data"},{"name":"R-jmv","description":"The Jamovi analyses"},{"name":"R-jmvconnect","description":"Connect to the Jamovi statistical spreadsheet"},{"name":"R-jmvcore","description":"Dependencies for the Jamovi framework"},{"name":"R-job","description":"Run R code as an RStudio job"},{"name":"R-joineR","description":"Joint modelling of repeated measurements and time-to-event data"},{"name":"R-joineRML","description":"Joint modelling of multivariate longitudinal data and time-to-event outcomes"},{"name":"R-joinet","description":"Multivariate elastic net regression"},{"name":"R-JointAI","description":"Joint Analysis and Imputation of Incomplete Data"},{"name":"R-jointDiag","description":"Joint approximate diagonalization of a set of square matrices"},{"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"},{"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"},{"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"},{"name":"R-kableExtra","description":"Construct complex table with kable and pipe syntax"},{"name":"R-kader","description":"Kernel adaptive density estimation and regression"},{"name":"R-kalmanfilter","description":"Kalman Filter"},{"name":"R-kangar00","description":"Kernel approaches for non-linear genetic association regression"},{"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"},{"name":"R-kDGLM","description":"Bayesian analysis of Dynamic Generalized Linear Models"}]}