HTTP 200 OK
Allow: GET, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept
{
"count": 42545,
"next": "https://ports.macports.org/api/v1/autocomplete/port/?format=api&page=672",
"previous": "https://ports.macports.org/api/v1/autocomplete/port/?format=api&page=670",
"results": [
{
"name": "R-baygel",
"description": "Bayesian estimators for Gaussian graphical models"
},
{
"name": "R-BB",
"description": "Solving and optimizing large-scale non-linear systems"
},
{
"name": "R-BBcor",
"description": "Bayesian bootstrapping correlations"
},
{
"name": "R-bbl",
"description": "Boltzmann Bayes Learner"
},
{
"name": "R-BBmisc",
"description": "Miscellaneous helper functions"
},
{
"name": "R-bbmle",
"description": "Tools for general maximum likelihood estimation"
},
{
"name": "R-bbnet",
"description": "Create simple predictive models on Bayesian Belief Networks"
},
{
"name": "R-bbotk",
"description": "Black-Box Optimization Toolkit"
},
{
"name": "R-bbreg",
"description": "Bessel and Beta regressions"
},
{
"name": "R-BBSSL",
"description": "Bayesian bootstrap spike-and-slab lassO"
},
{
"name": "R-BCA1SG",
"description": "Block coordinate ascent with one-step generalized Rosen algorithm"
},
{
"name": "R-BCDAG",
"description": "Bayesian structure and causal learning of Gaussian directed graphs"
},
{
"name": "R-BCEE",
"description": "Bayesian causal effect estimation algorithm"
},
{
"name": "R-bcgam",
"description": "Bayesian constrained generalised linear models"
},
{
"name": "R-BCHM",
"description": "Clinical trial calculation based on BCHM design"
},
{
"name": "R-bcp",
"description": "Bayesian analysis of change point problems"
},
{
"name": "R-bcROCsurface",
"description": "Bias-corrected methods for estimating the ROC surface of continuous diagnostic tests"
},
{
"name": "R-BCSub",
"description": "Bayesian semi-parametric factor analysis model for subtype identification (clustering)"
},
{
"name": "R-bda",
"description": "Binned Data Analysis"
},
{
"name": "R-bde",
"description": "Bounded Density Estimation"
},
{
"name": "R-BDEsize",
"description": "Efficient determination of sample size in balanced design of experiments"
},
{
"name": "R-BDgraph",
"description": "Bayesian structure learning in graphical models using birth-death MCMC"
},
{
"name": "R-bdlim",
"description": "Bayesian Distributed Lag Interaction Models"
},
{
"name": "R-bdsmatrix",
"description": "Routines for block diagonal symmetric matrices"
},
{
"name": "R-beachmat",
"description": "Compiling Bioconductor to handle each matrix type"
},
{
"name": "R-beanplot",
"description": "Visualization via beanplots"
},
{
"name": "R-beanz",
"description": "Bayesian analysis of heterogeneous treatment effect"
},
{
"name": "R-beast",
"description": "Bayesian estimation of change-points in the slope of multivariate time-series"
},
{
"name": "R-beepr",
"description": "Easily play notification sounds on any platform"
},
{
"name": "R-beeswarm",
"description": "The bee swarm plot, an alternative to stripchart"
},
{
"name": "R-bellreg",
"description": "Count regression models based on the Bell distribution"
},
{
"name": "R-bench",
"description": "High-precision timing of R expressions"
},
{
"name": "R-benchden",
"description": "28 benchmark densities from Berlinet–Devroye (1994)"
},
{
"name": "R-benchmarkme",
"description": "Crowd-sourced system benchmarks"
},
{
"name": "R-benchmarkmeData",
"description": "Crowd-sourced benchmarks from running the benchmarkme package"
},
{
"name": "R-benchr",
"description": "High-precision measurement of R expressions execution time"
},
{
"name": "R-BEND",
"description": "Bayesian Estimation of Non-linear Data (BEND)"
},
{
"name": "R-BeQut",
"description": "Bayesian estimation for quantile regression mixed models"
},
{
"name": "R-Bergm",
"description": "Bayesian Exponential Random Graph Models"
},
{
"name": "R-berryFunctions",
"description": "Functions collection related to plotting and hydrology"
},
{
"name": "R-Bessel",
"description": "Computations and approximations for Bessel functions"
},
{
"name": "R-bestglm",
"description": "Best subset GLM and regression utilities"
},
{
"name": "R-betaBayes",
"description": "Bayesian Beta regression"
},
{
"name": "R-betacal",
"description": "Fit beta calibration models and obtain calibrated probabilities from them"
},
{
"name": "R-betafunctions",
"description": "Functions for working with two- and four-parameter Beta probability distributions and psychometric analysis of classifications"
},
{
"name": "R-betaMC",
"description": "Monte Carlo for regression effect sizes"
},
{
"name": "R-betaNB",
"description": "Bootstrap for regression effect sizes"
},
{
"name": "R-BetaPASS",
"description": "Calculate power and sample size with Beta regression"
},
{
"name": "R-betareg",
"description": "Testing linear regression models"
},
{
"name": "R-betategarch",
"description": "Simulation, estimation and forecasting of Beta-Skew-t-EGARCH models"
}
]
}