Implement some deep learning architectures and neural network algorithms, including BP,RBM,DBN,Deep autoencoder and so on.
The CRAN check results and where your package stands in the CRAN submission queue in your R terminal.
This package provides a path-following algorithm for L1 regularized generalized linear models and Cox proportional hazards model.
This package provides basic graphing functions to fully demonstrate point-to-point connections in a polar coordinate space.
Calculate Hopkins statistic to assess the clusterability of data. See Wright (2023) <doi:10.32614/RJ-2022-055>.
R interface to access the web services of the ICES Stock Assessment Graphs database <https://sg.ices.dk>.
This package contains bibliographic information for the U.S. Geological Survey (USGS) Idaho National Laboratory (INL) Project Office.
Create tile grid maps, which are like choropleth maps except each region is represented with equal visual space.
This package performs matrix skew-t parameter estimation, Gallaugher and McNicholas (2017) <doi: 10.1002/sta4.143>.
This package provides a database containing the names of the babies born in Quebec between 1980 and 2020.
Create sliders from left, right, top and bottom which may include any html or Shiny input or output.
This package provides functions for conventionally formatting descriptive stats, reshaping data frames and formatting R output as HTML.
L2 penalized logistic regression for both continuous and discrete predictors, with forward stagewise/forward stepwise variable selection procedure.
This package provides a sparklyr extension that enables reading and writing TensorFlow TFRecord files via Apache Spark'.
Implementation of the shuffle estimator, a non-parametric estimator for signal and noise variance under mild noise correlations.
(guix-science-nonfree packages bioconductor)This package provides more than 9900 annotated position frequency matrices from 14 public sources, for multiple organisms.
The unmodified Linux kernel, including nonfree blobs, for running Guix System on hardware which requires nonfree software to function.
Meta-analysis is widely used to summarize estimated effects sizes across multiple statistical tests. Standard fixed and random effect meta-analysis methods assume that the estimated of the effect sizes are statistically independent. Here we relax this assumption and enable meta-analysis when the correlation matrix between effect size estimates is known.
Improves simultaneous inference under dependence of tests by estimating a collapsed null distribution through resampling. Accounting for the dependence between tests increases the power while reducing the variability of the false discovery proportion. This dependence is common in genomics applications, e.g. when combining flow cytometry measurements with microbiome sequence counts.
This package provides tools for randomization-based inference. Current focus is on the d^2 omnibus test of differences of means following Hansen and Bowers (2008) <doi:10.1214/08-STS254> . This test is useful for assessing balance in matched observational studies or for analysis of outcomes in block-randomized experiments.
This package provides tools for preprocessing and processing canopy photographs with support for raw data reading. Provides methods to address variability in sky brightness and to mitigate errors from image acquisition in non-diffuse light. Works with all types of fish-eye lenses, and some methods also apply to conventional lenses.
The APT Package Management System provides Debian and Debian-derived Linux systems with a powerful system to resolve package dependencies. This package offers access directly from R. This can only work on a system with a suitable libapt-pkg-dev installation so functionality is curtailed if such a library is not found.
Encode network data as strings of printable ASCII characters. Implemented functions include encoding and decoding adjacency matrices, edgelists, igraph, and network objects to/from formats graph6', sparse6', and digraph6'. The formats and methods are described in McKay, B.D. and Piperno, A (2014) <doi:10.1016/j.jsc.2013.09.003>.
Implementation of an algorithm in two steps to estimate parameters of a model whose latent dynamics are inferred through latent processes, jointly regularized. This package uses Monolix software (<https://monolixsuite.slp-software.com/>), which provide robust statistical method for non-linear mixed effects modeling. Monolix must have been installed prior to use.