conda-forge / packages

Package Name Access Summary Updated
r-tmb public With this tool, a user should be able to quickly implement complex random effect models through simple C++ templates. The package combines 'CppAD' (C++ automatic differentiation), 'Eigen' (templated matrix-vector library) and 'CHOLMOD' (sparse matrix routines available from R) to obtain an efficient implementation of the applied Laplace approximation with exact derivatives. Key features are: Automatic sparseness detection, parallelism through 'BLAS' and parallel user templates. 2019-06-19
r-stanheaders public The C++ header files of the Stan project are provided by this package, but it contains no R code or function documentation. There is a shared object containing part of the 'CVODES' library, but it is not accessible from R. 'StanHeaders' is only useful for developers who want to utilize the 'LinkingTo' directive of their package's DESCRIPTION file to build on the Stan library without incurring unnecessary dependencies. The Stan project develops a probabilistic programming language that implements full or approximate Bayesian statistical inference via Markov Chain Monte Carlo or 'variational' methods and implements (optionally penalized) maximum likelihood estimation via optimization. The Stan library includes an advanced automatic differentiation scheme, 'templated' statistical and linear algebra functions that can handle the automatically 'differentiable' scalar types (and doubles, 'ints', etc.), and a parser for the Stan language. The 'rstan' package provides user-facing R functions to parse, compile, test, estimate, and analyze Stan models. 2019-06-19
r-rrcov public Robust Location and Scatter Estimation and Robust Multivariate Analysis with High Breakdown Point. 2019-06-19
r-mvtnorm public Computes multivariate normal and t probabilities, quantiles, random deviates and densities. 2019-06-19
libcomcat public Python wrapper around ANSS ComCat API (plus tools). 2019-06-19
r-ranger public A fast implementation of Random Forests, particularly suited for high dimensional data. Ensembles of classification, regression, survival and probability prediction trees are supported. Data from genome-wide association studies can be analyzed efficiently. In addition to data frames, datasets of class 'gwaa.data' (R package 'GenABEL') and 'dgCMatrix' (R package 'Matrix') can be directly analyzed. 2019-06-19
r-registry public Provides a generic infrastructure for creating and using registries. 2019-06-19
r-pls public Multivariate regression methods Partial Least Squares Regression (PLSR), Principal Component Regression (PCR) and Canonical Powered Partial Least Squares (CPPLS). 2019-06-19
r-qvcalc public Functions to compute quasi variances and associated measures of approximation error. 2019-06-19
r-elliptic public A suite of elliptic and related functions including Weierstrass and Jacobi forms. Also includes various tools for manipulating and visualizing complex functions. 2019-06-19
r-cluster public Methods for Cluster analysis. Much extended the original from Peter Rousseeuw, Anja Struyf and Mia Hubert, based on Kaufman and Rousseeuw (1990) "Finding Groups in Data". 2019-06-19
featuretools public a framework for automated feature engineering 2019-06-19
nbgitpuller public Notebook Extension to do one-way synchronization of git repositories 2019-06-19
r-bayesm public Covers many important models used in marketing and micro-econometrics applications. The package includes: Bayes Regression (univariate or multivariate dep var), Bayes Seemingly Unrelated Regression (SUR), Binary and Ordinal Probit, Multinomial Logit (MNL) and Multinomial Probit (MNP), Multivariate Probit, Negative Binomial (Poisson) Regression, Multivariate Mixtures of Normals (including clustering), Dirichlet Process Prior Density Estimation with normal base, Hierarchical Linear Models with normal prior and covariates, Hierarchical Linear Models with a mixture of normals prior and covariates, Hierarchical Multinomial Logits with a mixture of normals prior and covariates, Hierarchical Multinomial Logits with a Dirichlet Process prior and covariates, Hierarchical Negative Binomial Regression Models, Bayesian analysis of choice-based conjoint data, Bayesian treatment of linear instrumental variables models, Analysis of Multivariate Ordinal survey data with scale usage heterogeneity (as in Rossi et al, JASA (01)), Bayesian Analysis of Aggregate Random Coefficient Logit Models as in BLP (see Jiang, Manchanda, Rossi 2009) For further reference, consult our book, Bayesian Statistics and Marketing by Rossi, Allenby and McCulloch (Wiley 2005) and Bayesian Non- and Semi-Parametric Methods and Applications (Princeton U Press 2014). 2019-06-19
botocore public Low-level, data-driven core of boto 3. 2019-06-19
spdlib public The Sorted Pulse Data Library (SPDLib) provides a format for storing and tools for processing discrete return and full waveform LiDAR data from airborne and terrestrial sensors. 2019-06-19
shap public A unified approach to explain the output of any machine learning model. 2019-06-19
rsgislib public The Remote Sensing and GIS software library (RSGISLib) is a collection of Python modules for processing remote sensing and GIS datasets. 2019-06-19
pysolar public A collection of Python libraries for simulating the irradiation of any point on earth by the sun 2019-06-19
r-bookdown public Output formats and utilities for authoring books and technical documents with R Markdown. 2019-06-19
r-bigstep public Selecting linear and generalized linear models for large data sets using modified stepwise procedure and modern selection criteria (like modifications of Bayesian Information Criterion). Selection can be performed on data which exceed RAM capacity. 2019-06-19
intltool public Internationalization Tool Collection. 2019-06-19
r-betareg public Beta regression for modeling beta-distributed dependent variables, e.g., rates and proportions. In addition to maximum likelihood regression (for both mean and precision of a beta-distributed response), bias-corrected and bias-reduced estimation as well as finite mixture models and recursive partitioning for beta regressions are provided. 2019-06-19
descarteslabs public Descartes Labs Python Library 2019-06-19
r-xts public Provide for uniform handling of R's different time-based data classes by extending zoo, maximizing native format information preservation and allowing for user level customization and extension, while simplifying cross-class interoperability. 2019-06-19
r-zip public Cross-Platform 'zip' Compression Library. A replacement for the 'zip' function, that does not require any additional external tools on any platform. 2019-06-19
r-awsmethods public Defines the method extract and provides 'openMP' support as needed in several packages. 2019-06-19
trimesh public Import, export, process, analyze and view triangular meshes. 2019-06-19
supermercado public Supercharged mercantile 2019-06-19
r-gmp public Multiple Precision Arithmetic (big integers and rationals, prime number tests, matrix computation), "arithmetic without limitations" using the C library GMP (GNU Multiple Precision Arithmetic). 2019-06-19
arabic_reshaper public Reconstruct Arabic sentences to be used in applications that don't support Arabic 2019-06-19
py-bash-completion public A framework for accessing bash completions from Python 2019-06-19
r-openxlsx public Simplifies the creation of Excel .xlsx files by providing a high level interface to writing, styling and editing worksheets. Through the use of 'Rcpp', read/write times are comparable to the 'xlsx' and 'XLConnect' packages with the added benefit of removing the dependency on Java. 2019-06-19
r-rcpparmadillo public 'Armadillo' is a templated C++ linear algebra library (by Conrad Sanderson) that aims towards a good balance between speed and ease of use. Integer, floating point and complex numbers are supported, as well as a subset of trigonometric and statistics functions. Various matrix decompositions are provided through optional integration with LAPACK and ATLAS libraries. The 'RcppArmadillo' package includes the header files from the templated 'Armadillo' library. Thus users do not need to install 'Armadillo' itself in order to use 'RcppArmadillo'. From release 7.800.0 on, 'Armadillo' is licensed under Apache License 2; previous releases were under licensed as MPL 2.0 from version 3.800.0 onwards and LGPL-3 prior to that; 'RcppArmadillo' (the 'Rcpp' bindings/bridge to Armadillo) is licensed under the GNU GPL version 2 or later, as is the rest of 'Rcpp'. Note that Armadillo requires a fairly recent compiler; for the g++ family at least version 4.6.* is required. 2019-06-19
r-maptools public Set of tools for manipulating geographic data. It includes binary access to 'GSHHG' shoreline files. The package also provides interface wrappers for exchanging spatial objects with packages such as 'PBSmapping', 'spatstat', 'maps', 'RArcInfo', and others. 2019-06-19
r-iso public Linear order and unimodal order (univariate) isotonic regression; bivariate isotonic regression with linear order on both variables. 2019-06-19
r-lmtest public A collection of tests, data sets, and examples for diagnostic checking in linear regression models. Furthermore, some generic tools for inference in parametric models are provided. 2019-06-19
sagelib public Open Source Mathematical Software 2019-06-19
r-ipred public Improved predictive models by indirect classification and bagging for classification, regression and survival problems as well as resampling based estimators of prediction error. 2019-06-19
r-hmisc public Contains many functions useful for data analysis, high-level graphics, utility operations, functions for computing sample size and power, importing and annotating datasets, imputing missing values, advanced table making, variable clustering, character string manipulation, conversion of R objects to LaTeX and html code, and recoding variables. 2019-06-19
r-plotrix public Lots of plots, various labeling, axis and color scaling functions. 2019-06-19
xmlschema public An XML Schema validator and decoder 2019-06-19
r-numderiv public Methods for calculating (usually) accurate numerical first and second order derivatives. Accurate calculations are done using 'Richardson''s' extrapolation or, when applicable, a complex step derivative is available. A simple difference method is also provided. Simple difference is (usually) less accurate but is much quicker than 'Richardson''s' extrapolation and provides a useful cross-check. Methods are provided for real scalar and vector valued functions. 2019-06-19
r-multcomp public Simultaneous tests and confidence intervals for general linear hypotheses in parametric models, including linear, generalized linear, linear mixed effects, and survival models. The package includes demos reproducing analyzes presented in the book "Multiple Comparisons Using R" (Bretz, Hothorn, Westfall, 2010, CRC Press). 2019-06-19
terraform-provider-digitalocean public The Terraform DigitalOcean provider 2019-06-19
terraform-provider-consul public The Terraform Consul provider 2019-06-19
ml_tooling public Modelling framework to simplify machine learning workflows 2019-06-19
pydantic public Data validation and settings management using python type hinting 2019-06-19
google-pasta public pasta is an AST-based Python refactoring library 2019-06-19
pysnooper public A poor man's debugger for Python. 2019-06-19
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