{"count":40951,"next":"https://ports.macports.org/api/v1/autocomplete/port/?format=json&page=643","previous":"https://ports.macports.org/api/v1/autocomplete/port/?format=json&page=641","results":[{"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"},{"name":"R-bettermc","description":"Enhanced fork-based parallelization"},{"name":"R-bezier","description":"Toolkit for Bezier curves and splines"},{"name":"R-bfast","description":"Breaks for Additive Season and Trend in time series"},{"name":"R-BFF","description":"Bayes Factor Functions"},{"name":"R-bfp","description":"Bayesian Fractional Polynomials"},{"name":"R-BFpack","description":"Flexible Bayes factor testing of scientific expectations"},{"name":"R-bgev","description":"Bimodal GEV distribution with location parameter"},{"name":"R-BGFD","description":"Bell-G and Complementary Bell-G family of distributions"},{"name":"R-BGGM","description":"Bayesian Gaussian Graphical Models"},{"name":"R-bggum","description":"Bayesian estimation of generalized graded unfolding model parameters"},{"name":"R-BGLR","description":"Bayesian Generalized Linear Regression"},{"name":"R-bgmm","description":"Gaussian mixture modelling algorithms and the belief-based mixture modelling"},{"name":"R-bgms","description":"Bayesian variable selection for networks of binary and/or ordinal variables"}]}