|
r-hier.part
|
public |
Partitioning of the independent and joint contributions of each variable in a multivariate data set, to a linear regression by hierarchical decomposition of goodness-of-fit measures of regressions using all subsets of predictors in the data set. (i.e., model (1), (2), ..., (N), (1,2), ..., (1,N), ..., (1,2,3,...,N)). A Z-score based estimate of the 'importance' of each predictor is provided by using a randomisation test.
|
2025-04-22 |
|
coreapi-cli
|
public |
An interactive command line client for Core API.
|
2025-04-22 |
|
python-coreapi
|
public |
Python client library for Core API.
|
2025-04-22 |
|
rx
|
public |
Reactive Extensions (Rx) for Python
|
2025-04-22 |
|
itypes
|
public |
Basic immutable container types for Python.
|
2025-04-22 |
|
python-coreschema
|
public |
Python interface to coreschema
|
2025-04-22 |
|
libbrial
|
public |
Brial - successor to PolyBoRi
|
2025-04-22 |
|
neunorm
|
public |
Neutron Imaging Normalization Library
|
2025-04-22 |
|
array2gif
|
public |
Write a 3-D NumPy array to a GIF, or an array of them to an animated GIF.
|
2025-04-22 |
|
jaydebeapi
|
public |
A Python DB-APIv2.0 compliant library for JDBC Drivers
|
2025-04-22 |
|
serializable
|
public |
Base class with serialization helpers for user-defined Python objects
|
2025-04-22 |
|
django-widget-tweaks
|
public |
Tweak the form field rendering in templates, not in python-level form definitions.
|
2025-04-22 |
|
trollsift
|
public |
String parser/formatter for PyTroll packages
|
2025-04-22 |
|
python-geotiepoints
|
public |
Interpolation of geographic tiepoints in Python
|
2025-04-22 |
|
pycoast
|
public |
Writing of coastlines, borders and rivers to images in Python
|
2025-04-22 |
|
cgroupspy
|
public |
Python library for managing cgroups
|
2025-04-22 |
|
r-mice
|
public |
Multiple imputation using Fully Conditional Specification (FCS) implemented by the MICE algorithm as described in Van Buuren and Groothuis-Oudshoorn (2011) <doi:10.18637/jss.v045.i03>. Each variable has its own imputation model. Built-in imputation models are provided for continuous data (predictive mean matching, normal), binary data (logistic regression), unordered categorical data (polytomous logistic regression) and ordered categorical data (proportional odds). MICE can also impute continuous two-level data (normal model, pan, second-level variables). Passive imputation can be used to maintain consistency between variables. Various diagnostic plots are available to inspect the quality of the imputations.
|
2025-04-22 |
|
cppheaderparser
|
public |
Parse C++ header files and generate a data structure representing the class
|
2025-04-22 |
|
bisonpp
|
public |
The original bison++ project, brought up to date with modern compilers
|
2025-04-22 |
|
datacache
|
public |
Helpers for transparently downloading datasets
|
2025-04-22 |
|
r-paco
|
public |
Procrustes analyses to infer co-phylogenetic matching between pairs of (ultrametric) phylogenetic trees.
|
2025-04-22 |
|
python_http_client
|
public |
SendGrid's Python HTTP Client for calling APIs
|
2025-04-22 |
|
w3g
|
public |
Access Warcraft 3 replay files from Python 2 or 3
|
2025-04-22 |
|
trollimage
|
public |
Pytroll imaging library
|
2025-04-22 |
|
memoized-property
|
public |
A simple python decorator for defining properties that only run their fget function once
|
2025-04-22 |
