| Favorites | Downloads | Artifact (owner / artifact) | Platforms |
|---|---|---|---|
| 1 | 893560 |
conda-forge / audioread 3.0.1multi-library, cross-platform audio decodingcopy
conda
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linux-64 linux-aarch64 linux-ppc64le osx-64 osx-arm64 win-32 win-64 |
| 1 | 188813 |
conda-forge / pandoc-crossref 0.3.17.1Pandoc filter for cross-referencescopy
conda
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linux-64 osx-64 osx-arm64 win-64 |
| 1 | 123493 |
conda-forge / pymde 0.1.18Minimum-Distortion Embeddingcopy
conda
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linux-64 osx-64 osx-arm64 |
| 1 | 98544 |
conda-forge / r-gtsummary 2.0.3Creates presentation-ready tables summarizing data sets, regression models, and more. The code to create the tables is concise and highly customizable. Data frames can be summarized with any function, e.g. mean(), median(), even user-written functions. Regression models are summarized and include the reference rows for categorical variables. Common regression models, such as logistic regression and Cox proportional hazards regression, are automatically identified and the tables are pre-filled with appropriate column headers.copy
conda
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noarch |
| 1 | 42290 |
conda-forge / r-spatialreg 1.2_3A collection of all the estimation functions for spatial cross-sectional models (on lattice/areal data using spatial weights matrices) contained up to now in 'spdep', 'sphet' and 'spse'. These model fitting functions include maximum likelihood methods for cross-sectional models proposed by 'Cliff' and 'Ord' (1973, ISBN:0850860369) and (1981, ISBN:0850860814), fitting methods initially described by 'Ord' (1975) <doi:10.1080/01621459.1975.10480272>. The models are further described by 'Anselin' (1988) <doi:10.1007/978-94-015-7799-1>. Spatial two stage least squares and spatial general method of moment models initially proposed by 'Kelejian' and 'Prucha' (1998) <doi:10.1023/A:1007707430416> and (1999) <doi:10.1111/1468-2354.00027> are provided. Impact methods and MCMC fitting methods proposed by 'LeSage' and 'Pace' (2009) <doi:10.1201/9781420064254> are implemented for the family of cross-sectional spatial regression models. Methods for fitting the log determinant term in maximum likelihood and MCMC fitting are compared by 'Bivand et al.' (2013) <doi:10.1111/gean.12008>, and model fitting methods by 'Bivand' and 'Piras' (2015) <doi:10.18637/jss.v063.i18>; both of these articles include extensive lists of references. 'spatialreg' >= 1.1-* correspond to 'spdep' >= 1.1-1, in which the model fitting functions are deprecated and pass through to 'spatialreg', but will mask those in 'spatialreg'. From versions 1.2-*, the functions will be made defunct in 'spdep'.copy
conda
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linux-64 osx-64 win-64 |
| 1 | 39649 |
bioconda / wiggletools 1.2.11The WiggleTools package allows genomewide data files to be manipulated as numerical functions, equipped with all the standard functional analysis operators (sum, product, product by a scalar, comparators), and derived statistics (mean, median, variance, stddev, t-test, Wilcoxon's rank sum test, etc).
conda
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linux-64 linux-aarch64 osx-64 |
| 1 | 30264 |
conda-forge / tsl_robin_map 1.3.0C++ fast hash map and hash set using robin hood hashingcopy
conda
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linux-64 linux-aarch64 linux-ppc64le osx-64 osx-arm64 win-64 |
| 1 | 26510 |
conda-forge / r-clustimpute 0.2.4This k-means algorithm is able to cluster data with missing values and as a by-product completes the data set. The implementation can deal with missing values in multiple variables and is computationally efficient since it iteratively uses the current cluster assignment to define a plausible distribution for missing value imputation. Weights are used to shrink early random draws for missing values (i.e., draws based on the cluster assignments after few iterations) towards the global mean of each feature. This shrinkage slowly fades out after a fixed number of iterations to reflect the increasing credibility of cluster assignments. See the vignette for details.copy
conda
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noarch |
| 1 | 26457 |
conda-forge / r-ggside 0.3.1The grammar of graphics as shown in 'ggplot2' has provided an expressive API for users to build plots. 'ggside' extends 'ggplot2' by allowing users to add graphical information about one of the main panel's axis using a familiar 'ggplot2' style API with tidy data. This package is particularly useful for visualizing metadata on a discrete axis, or summary graphics on a continuous axis such as a boxplot or a density distribution.copy
conda
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noarch |
| 1 | 22193 |
conda-forge / r-rglpk 0.6_5.1R interface to the GNU Linear Programming Kit. 'GLPK' is open source software for solving large-scale linear programming (LP), mixed integer linear programming ('MILP') and other related problems.copy
conda
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linux-64 osx-64 win-64 |
| 1 | 20555 |
conda-forge / conda-ecosystem-user-package-isolation 1.0Prevent python and R from searching for packages outside of the current environment
conda
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linux-64 linux-aarch64 linux-ppc64le osx-64 osx-arm64 win-64 |
| 1 | 20388 |
conda-forge / r-glpkapi 1.3.4R Interface to C API of GLPK, depends on GLPK Version >= 4.42.copy
conda
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linux-64 osx-64 win-64 |
| 1 | 18802 |
conda-forge / r-expss 0.11.6Package computes and displays tables with support for 'SPSS'-style labels, multiple and nested banners, weights, multiple-response variables and significance testing. There are facilities for nice output of tables in 'knitr', 'Shiny', '*.xlsx' files, R and 'Jupyter' notebooks. Methods for labelled variables add value labels support to base R functions and to some functions from other packages. Additionally, the package brings popular data transformation functions from 'SPSS' Statistics and 'Excel': 'RECODE', 'COUNT', 'COMPUTE', 'DO IF', 'COUNTIF', 'VLOOKUP' and etc. These functions are very useful for data processing in marketing research surveys. Package intended to help people to move data processing from 'Excel' and 'SPSS' to R.copy
conda
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noarch |
| 1 | 10182 |
conda-forge / r-tidygate 1.0.14It interactively or programmatically label points within custom gates on two dimensions <https://github.com/stemangiola/tidygate>. The information is added to your tibble. It is based on the package 'gatepoints' from Wajid Jawaid (who is also author of this package). The code of 'gatepoints' was nto integrated in 'tidygate'. The benefits are (i) in interactive mode you can draw your gates on extensive 'ggplot'-like scatter plots; (ii) you can draw multiple gates; and (iii) you can save your gates and apply the programmatically.copy
conda
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noarch |
| 1 | 9629 |
conda-forge / r-generalizedhyperbolic 0.8_4Functions for the hyperbolic and related distributions. Density, distribution and quantile functions and random number generation are provided for the hyperbolic distribution, the generalized hyperbolic distribution, the generalized inverse Gaussian distribution and the skew-Laplace distribution. Additional functionality is provided for the hyperbolic distribution, normal inverse Gaussian distribution and generalized inverse Gaussian distribution, including fitting of these distributions to data. Linear models with hyperbolic errors may be fitted using hyperblmFit.copy
conda
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noarch |
| 1 | 9586 |
conda-forge / r-skewhyperbolic 0.4_0Functions are provided for the density function, distribution function, quantiles and random number generation for the skew hyperbolic t-distribution. There are also functions that fit the distribution to data. There are functions for the mean, variance, skewness, kurtosis and mode of a given distribution and to calculate moments of any order about any centre. To assess goodness of fit, there are functions to generate a Q-Q plot, a P-P plot and a tail plot.copy
conda
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noarch |
| 1 | 9516 |
conda-forge / r-variancegamma 0.4_2Provides functions for the variance gamma distribution. Density, distribution and quantile functions. Functions for random number generation and fitting of the variance gamma to data. Also, functions for computing moments of the variance gamma distribution of any order about any location. In addition, there are functions for checking the validity of parameters and to interchange different sets of parameterizations for the variance gamma distribution.copy
conda
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noarch |
| 1 | 9367 |
conda-forge / r-normallaplace 0.3_0Functions for the normal Laplace distribution. The package is under development and provides only limited functionality. Density, distribution and quantile functions, random number generation, and moments are provided.copy
conda
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noarch |
| 1 | 8684 |
conda-forge / r-ggmosaic 0.3.3Mosaic plots in the 'ggplot2' framework. Mosaic plot functionality is provided in a single 'ggplot2' layer by calling the geom 'mosaic'.copy
conda
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noarch |
| 1 | 8537 |
conda-forge / r-productplots 0.1.1Framework for visualising tables of counts, proportions and probabilities. The framework is called product plots, alluding to the computation of area as a product of height and width, and the statistical concept of generating a joint distribution from the product of conditional and marginal distributions. The framework, with extensions, is sufficient to encompass over 20 visualisations previously described in fields of statistical graphics and 'infovis', including bar charts, mosaic plots, 'treemaps', equal area plots and fluctuation diagrams.copy
conda
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noarch |
| 1 | 74 |
merv / r-scutrboot 0.3.0A set of bootstrap-based statistical methods for analyzing 3\' UTR quantification data derived from single-cell RNA-sequencing.
conda
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linux-64 noarch osx-64 |
