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r-capushe
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public |
Calibration of penalized criteria for model selection. The calibration methods available are based on the slope heuristics.
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2025-04-22 |
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r-dismo
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public |
Functions for species distribution modeling, that is, predicting entire geographic distributions form occurrences at a number of sites and the environment at these sites.
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2025-04-22 |
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r-fts
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public |
fast operations for time series objects
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2025-04-22 |
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pscript
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public |
library for transpiling Python code to JavaScript.
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2025-04-22 |
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molvs
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public |
Molecule Validation and Standardization
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2025-04-22 |
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logging_exceptions
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public |
Self-logging exceptions: Attach log messages to exceptions and output them conditionally.
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2025-04-22 |
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cyclus-d3ploy
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public |
Demand Driven Deployment for Cyclus
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2025-04-22 |
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r-text2vec
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public |
Fast and memory-friendly tools for text vectorization, topic modeling (LDA, LSA), word embeddings (GloVe), similarities. This package provides a source-agnostic streaming API, which allows researchers to perform analysis of collections of documents which are larger than available RAM. All core functions are parallelized to benefit from multicore machines.
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2025-04-22 |
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r-here
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public |
Constructs paths to your project's files. The 'here()' function uses a reasonable heuristics to find your project's files, based on the current working directory at the time when the package is loaded. Use it as a drop-in replacement for 'file.path()', it will always locate the files relative to your project root.
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2025-04-22 |
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r-glmmtmb
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public |
Fit linear and generalized linear mixed models with various extensions, including zero-inflation. The models are fitted using maximum likelihood estimation via 'TMB' (Template Model Builder). Random effects are assumed to be Gaussian on the scale of the linear predictor and are integrated out using the Laplace approximation. Gradients are calculated using automatic differentiation.
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2025-04-22 |
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python-box
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public |
Python dictionaries with recursive dot notation access
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2025-04-22 |
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pyprism
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public |
A python tool for Polymer Reference Interactions Site Model (PRISM) calculations
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2025-04-22 |
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py-bash-completion
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public |
A framework for accessing bash completions from Python
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2025-04-22 |
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jaws
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public |
Justify idiosyncratic ASCII AWS formats into analyzable netCDF formats.
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2025-04-22 |
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dialite
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public |
small library to show simple dialogs to the user, without the need for a heavy GUI toolkit.
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2025-04-22 |
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contextvars
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public |
PEP 567 Backport
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2025-04-22 |
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betse
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public |
BETSE, the BioElectric Tissue Simulation Engine
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2025-04-22 |
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cftime
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public |
Time-handling functionality from netcdf4-python
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2025-04-22 |
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libtasn1
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public |
Libtasn1 is the ASN.1 library used by GnuTLS, p11-kit and some other packages
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2025-04-22 |
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backports.tempfile
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public |
Backports of new features in Python's tempfile module
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2025-04-22 |
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imagingreso
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public |
a tool to simulate neutron resonance signal for neutron resonance imaging
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2025-04-22 |
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r-skmeans
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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.
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2025-04-22 |
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r-conicfit
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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.
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2025-04-22 |
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r-mertools
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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.
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2025-04-22 |
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r-mirt
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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.
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2025-04-22 |
