{"count":40910,"next":"https://ports.macports.org/api/v1/autocomplete/port/?format=json&page=666","previous":"https://ports.macports.org/api/v1/autocomplete/port/?format=json&page=664","results":[{"name":"R-fmcsR","description":"Mismatch-tolerant maximum common substructure searching"},{"name":"R-FME","description":"Flexible modelling environment for inverse modelling, sensitivity, identifiability and Monte Carlo analysis"},{"name":"R-fmeffects","description":"Model-agnostic interpretations with forward marginal effects"},{"name":"R-fmesher","description":"Triangle meshes and related geometry tools"},{"name":"R-fmsb","description":"Practices of Medical and Health Data Analysis using R"},{"name":"R-FMStable","description":"Finite Moment Stable Distributions"},{"name":"R-fmtr","description":"Easily apply formats to data"},{"name":"R-fMultivar","description":"Modeling of multivariate financial return distributions"},{"name":"R-fmx","description":"Finite Mixture Parametrization"},{"name":"R-fnets","description":"Factor-adjusted network estimation and forecasting for high-dimensional time series"},{"name":"R-FNN","description":"Fast Nearest Neighbor search algorithms and applications"},{"name":"R-fNonlinear","description":"Rmetrics – non-linear and chaotic time series modelling"},{"name":"R-fntl","description":"Numerical tools for Rcpp and Lambda functions"},{"name":"R-foghorn","description":"R package to summarize CRAN check results in the Terminal"},{"name":"R-fontawesome","description":"Easily work with Font Awesome icons"},{"name":"R-fontBitstreamVera","description":"Bitstream Vera Fonts"},{"name":"R-fontLiberation","description":"Liberation Fonts"},{"name":"R-fontquiver","description":"Set of installed fonts"},{"name":"R-forcats","description":"Tools for working with categorical variables (factors)"},{"name":"R-foreach","description":"Provides foreach looping construct"},{"name":"R-ForeCA","description":"Forecastable Component Analysis"},{"name":"R-forecast","description":"Forecasting functions for time series and linear models"},{"name":"R-forecTheta","description":"Forecasting time series by Theta models"},{"name":"R-foreign","description":"Read and write data in other statistical software formats"},{"name":"R-forestplot","description":"Advanced forest plot using grid graphics"},{"name":"R-forestploter","description":"Create flexible forest plot"},{"name":"R-ForestTools","description":"Tools for analyzing remote sensing forest data"},{"name":"R-forge","description":"Helper functions with a consistent interface to coerce and verify the types and shapes of values for input checking."},{"name":"R-formatR","description":"Format R code automatically"},{"name":"R-formattable","description":"Create formattable data structures"},{"name":"R-formatters","description":"ASCII formatting for values and tables"},{"name":"R-Formula","description":"Extended model formulas"},{"name":"R-formula.tools","description":"Programmatic utilities for manipulating formulas, expressions, calls, assignments and other R objects"},{"name":"R-forsearch","description":"Diagnostic analysis using forward search procedure"},{"name":"R-fortranfctpassing","description":"Communication between Fortran, Rcpp and R. Passing R or Fortran user code to Fortran code from a package."},{"name":"R-fortunes","description":"R Fortunes"},{"name":"R-forward","description":"Robust analysis using forward search in linear and generalized linear regression models"},{"name":"R-fossil","description":"Palæoecological and palæogeographical analysis tools"},{"name":"R-fourierin","description":"Numeric Fourier Integrals"},{"name":"R-fpc","description":"Flexible Procedures for Clustering"},{"name":"R-fplot","description":"Automatic distribution graphs using formulas"},{"name":"R-fplyr","description":"Apply functions to blocks of files"},{"name":"R-fpop","description":"Segmentation using optimal partitioning and function pruning"},{"name":"R-fpow","description":"Compute the non-centrality parameter of the non-central F distribution"},{"name":"R-fpp","description":"Data for Forecasting: Principles and Practice"},{"name":"R-fpp2","description":"Data for Forecasting: Principles and Practice (2nd ed.)"},{"name":"R-frab","description":"Alternative interpretation of named vectors"},{"name":"R-fracdiff","description":"Fractionally differenced ARIMA aka ARFIMA(P,d,q) models"},{"name":"R-FracKrigingR","description":"Spatial multivariate data modelling"},{"name":"R-fractalRegression","description":"Various functions for performing fractal and multifractal analysis including performing fractal regression"}]}