pyprism
|
public |
A python tool for Polymer Reference Interactions Site Model (PRISM) calculations
|
2025-04-22 |
py-bash-completion
|
public |
A framework for accessing bash completions from Python
|
2025-04-22 |
jaws
|
public |
Justify idiosyncratic ASCII AWS formats into analyzable netCDF formats.
|
2025-04-22 |
dialite
|
public |
small library to show simple dialogs to the user, without the need for a heavy GUI toolkit.
|
2025-04-22 |
contextvars
|
public |
PEP 567 Backport
|
2025-04-22 |
betse
|
public |
BETSE, the BioElectric Tissue Simulation Engine
|
2025-04-22 |
cftime
|
public |
Time-handling functionality from netcdf4-python
|
2025-04-22 |
libtasn1
|
public |
Libtasn1 is the ASN.1 library used by GnuTLS, p11-kit and some other packages
|
2025-04-22 |
backports.tempfile
|
public |
Backports of new features in Python's tempfile module
|
2025-04-22 |
imagingreso
|
public |
a tool to simulate neutron resonance signal for neutron resonance imaging
|
2025-04-22 |
r-skmeans
|
public |
Algorithms to compute spherical k-means partitions. Features several methods, including a genetic and a fixed-point algorithm and an interface to the CLUTO vcluster program.
|
2025-04-22 |
r-conicfit
|
public |
Geometric circle fitting with Levenberg-Marquardt (a, b, R), Levenberg-Marquardt reduced (a, b), Landau, Spath and Chernov-Lesort. Algebraic circle fitting with Taubin, Kasa, Pratt and Fitzgibbon-Pilu-Fisher. Geometric ellipse fitting with ellipse LMG (geometric parameters) and conic LMA (algebraic parameters). Algebraic ellipse fitting with Fitzgibbon-Pilu-Fisher and Taubin.
|
2025-04-22 |
r-mertools
|
public |
Provides methods for extracting results from mixed-effect model objects fit with the 'lme4' package. Allows construction of prediction intervals efficiently from large scale linear and generalized linear mixed-effects models.
|
2025-04-22 |
r-mirt
|
public |
Analysis of dichotomous and polytomous response data using unidimensional and multidimensional latent trait models under the Item Response Theory paradigm (Chalmers (2012) <doi:10.18637/jss.v048.i06>). Exploratory and confirmatory models can be estimated with quadrature (EM) or stochastic (MHRM) methods. Confirmatory bi-factor and two-tier analyses are available for modeling item testlets. Multiple group analysis and mixed effects designs also are available for detecting differential item and test functioning as well as modeling item and person covariates. Finally, latent class models such as the DINA, DINO, multidimensional latent class, and several other discrete latent variable models, including mixture and zero-inflated response models, are supported.
|
2025-04-22 |
r-sem
|
public |
Functions for fitting general linear structural equation models (with observed and latent variables) using the RAM approach, and for fitting structural equations in observed-variable models by two-stage least squares.
|
2025-04-22 |
r-mi
|
public |
The mi package provides functions for data manipulation, imputing missing values in an approximate Bayesian framework, diagnostics of the models used to generate the imputations, confidence-building mechanisms to validate some of the assumptions of the imputation algorithm, and functions to analyze multiply imputed data sets with the appropriate degree of sampling uncertainty.
|
2025-04-22 |
r-prediction
|
public |
A one-function package containing 'prediction()', a type-safe alternative to 'predict()' that always returns a data frame. The 'summary()' method provides a data frame with average predictions, possibly over counterfactual versions of the data (a la the 'margins' command in 'Stata'). Marginal effect estimation is provided by the related package, 'margins' <https://cran.r-project.org/package=margins>. The package currently supports common model types (e.g., "lm", "glm") from the 'stats' package, as well as numerous other model classes from other add-on packages. See the README or main package documentation page for a complete listing.
|
2025-04-22 |
r-blme
|
public |
Maximum a posteriori estimation for linear and generalized linear mixed-effects models in a Bayesian setting. Extends 'lme4' by Douglas Bates, Martin Maechler, Ben Bolker, and Steve Walker.
|
2025-04-22 |
trafaret
|
public |
Ultimate transformation library that supports validation, contexts and aiohttp
|
2025-04-22 |
r-semtools
|
public |
Provides useful tools for structural equation modeling.
|
2025-04-22 |
r-mvnormtest
|
public |
Generalization of shapiro-wilk test for multivariate variables.
|
2025-04-22 |
r-bayesfactor
|
public |
A suite of functions for computing various Bayes factors for simple designs, including contingency tables, one- and two-sample designs, one-way designs, general ANOVA designs, and linear regression.
|
2025-04-22 |
r-sparsepp
|
public |
Provides interface to 'sparsepp' - fast, memory efficient hash map. It is derived from Google's excellent 'sparsehash' implementation. We believe 'sparsepp' provides an unparalleled combination of performance and memory usage, and will outperform your compiler's unordered_map on both counts. Only Google's 'dense_hash_map' is consistently faster, at the cost of much greater memory usage (especially when the final size of the map is not known in advance).
|
2025-04-22 |
r-mlapi
|
public |
Provides 'R6' abstract classes for building machine learning models with 'scikit-learn' like API. <http://scikit-learn.org/> is a popular module for 'Python' programming language which design became de facto a standard in industry for machine learning tasks.
|
2025-04-22 |
r-gnm
|
public |
Functions to specify and fit generalized nonlinear models, including models with multiplicative interaction terms such as the UNIDIFF model from sociology and the AMMI model from crop science, and many others. Over-parameterized representations of models are used throughout; functions are provided for inference on estimable parameter combinations, as well as standard methods for diagnostics etc.
|
2025-04-22 |