Showing 17 of total 17 results (show query)
runehaubo
lmerTest:Tests in Linear Mixed Effects Models
Provides p-values in type I, II or III anova and summary tables for lmer model fits (cf. lme4) via Satterthwaite's degrees of freedom method. A Kenward-Roger method is also available via the pbkrtest package. Model selection methods include step, drop1 and anova-like tables for random effects (ranova). Methods for Least-Square means (LS-means) and tests of linear contrasts of fixed effects are also available.
Maintained by Rune Haubo Bojesen Christensen. Last updated 4 years ago.
52 stars 13.09 score 13k scripts 91 dependents
mhahsler
stream:Infrastructure for Data Stream Mining
A framework for data stream modeling and associated data mining tasks such as clustering and classification. The development of this package was supported in part by NSF IIS-0948893, NSF CMMI 1728612, and NIH R21HG005912. Hahsler et al (2017) <doi:10.18637/jss.v076.i14>.
Maintained by Michael Hahsler. Last updated 16 days ago.
data-stream-clusteringdatastreamstream-miningcpp
39 stars 10.05 score 132 scripts 3 dependents
azure
azuremlsdk:Interface to the 'Azure Machine Learning' 'SDK'
Interface to the 'Azure Machine Learning' Software Development Kit ('SDK'). Data scientists can use the 'SDK' to train, deploy, automate, and manage machine learning models on the 'Azure Machine Learning' service. To learn more about 'Azure Machine Learning' visit the website: <https://docs.microsoft.com/en-us/azure/machine-learning/service/overview-what-is-azure-ml>.
Maintained by Diondra Peck. Last updated 3 years ago.
amlcomputeazureazure-machine-learningazuremldsimachine-learningrstudiosdk-r
105 stars 8.91 score 221 scripts
rjdverse
RJDemetra:Interface to 'JDemetra+' Seasonal Adjustment Software
Interface around 'JDemetra+' (<https://github.com/jdemetra/jdemetra-app>), the seasonal adjustment software officially recommended to the members of the European Statistical System (ESS) and the European System of Central Banks. It offers full access to all options and outputs of 'JDemetra+', including the two leading seasonal adjustment methods TRAMO/SEATS+ and X-12ARIMA/X-13ARIMA-SEATS.
Maintained by Alain Quartier-la-Tente. Last updated 21 days ago.
53 stars 8.67 score 128 scripts 5 dependents
bioc
musicatk:Mutational Signature Comprehensive Analysis Toolkit
Mutational signatures are carcinogenic exposures or aberrant cellular processes that can cause alterations to the genome. We created musicatk (MUtational SIgnature Comprehensive Analysis ToolKit) to address shortcomings in versatility and ease of use in other pre-existing computational tools. Although many different types of mutational data have been generated, current software packages do not have a flexible framework to allow users to mix and match different types of mutations in the mutational signature inference process. Musicatk enables users to count and combine multiple mutation types, including SBS, DBS, and indels. Musicatk calculates replication strand, transcription strand and combinations of these features along with discovery from unique and proprietary genomic feature associated with any mutation type. Musicatk also implements several methods for discovery of new signatures as well as methods to infer exposure given an existing set of signatures. Musicatk provides functions for visualization and downstream exploratory analysis including the ability to compare signatures between cohorts and find matching signatures in COSMIC V2 or COSMIC V3.
Maintained by Joshua D. Campbell. Last updated 5 months ago.
softwarebiologicalquestionsomaticmutationvariantannotation
13 stars 6.97 score 20 scripts
spsanderson
tidyAML:Automatic Machine Learning with 'tidymodels'
The goal of this package will be to provide a simple interface for automatic machine learning that fits the 'tidymodels' framework. The intention is to work for regression and classification problems with a simple verb framework.
Maintained by Steven Sanderson. Last updated 11 months ago.
automatic-machine-learningautomlclassificationmachine-learningparsnipr-languager-programmingregressiontidytidymodelstidyverse
68 stars 6.56 score 36 scripts 1 dependents
victor-navarro
calmr:Canonical Associative Learning Models and their Representations
Implementations of canonical associative learning models, with tools to run experiment simulations, estimate model parameters, and compare model representations. Experiments and results are represented using S4 classes and methods.
Maintained by Victor Navarro. Last updated 10 months ago.
3 stars 6.40 score 17 scripts
cvasi-tktd
cvasi:Calibration, Validation, and Simulation of TKTD Models
Eases the use of ecotoxicological effect models. Can simulate common toxicokinetic-toxicodynamic (TK/TD) models such as General Unified Threshold models of Survival (GUTS) and Lemna. It can derive effects and effect profiles (EPx) from scenarios. It supports the use of 'tidyr' workflows employing the pipe symbol. Time-consuming tasks can be parallelized.
Maintained by Nils Kehrein. Last updated 9 days ago.
ecotoxicologymodelingsimulation
2 stars 6.27 score 12 scripts
jchrom
trelloR:Access the Trello API
An R client for the Trello API. Supports free-tier features such as access to private boards, creating and updating cards and other resources, and downloading data in a structured way.
Maintained by Jakub Chromec. Last updated 2 years ago.
42 stars 6.18 score 24 scripts
jtimonen
lgpr:Longitudinal Gaussian Process Regression
Interpretable nonparametric modeling of longitudinal data using additive Gaussian process regression. Contains functionality for inferring covariate effects and assessing covariate relevances. Models are specified using a convenient formula syntax, and can include shared, group-specific, non-stationary, heterogeneous and temporally uncertain effects. Bayesian inference for model parameters is performed using 'Stan'. The modeling approach and methods are described in detail in Timonen et al. (2021) <doi:10.1093/bioinformatics/btab021>.
Maintained by Juho Timonen. Last updated 7 months ago.
bayesian-inferencegaussian-processeslongitudinal-datastancpp
25 stars 5.94 score 69 scripts
pmszulc
bigstep:Stepwise Selection for Large Data Sets
Selecting linear and generalized linear models for large data sets using modified stepwise procedure and modern selection criteria (like modifications of Bayesian Information Criterion). Selection can be performed on data which exceed RAM capacity. Bogdan et al., (2004) <doi:10.1534/genetics.103.021683>.
Maintained by Piotr Szulc. Last updated 18 days ago.
2 stars 5.18 score 51 scripts 1 dependentsazure
AzureVision:Interface to Azure Computer Vision Services
An interface to 'Azure Computer Vision' <https://docs.microsoft.com/azure/cognitive-services/Computer-vision/Home> and 'Azure Custom Vision' <https://docs.microsoft.com/azure/cognitive-services/custom-vision-service/home>, building on the low-level functionality provided by the 'AzureCognitive' package. These services allow users to leverage the cloud to carry out visual recognition tasks using advanced image processing models, without needing powerful hardware of their own. Part of the 'AzureR' family of packages.
Maintained by Hong Ooi. Last updated 4 years ago.
azure-cognitive-servicesazure-sdk-rcomputer-visioncustom-vision
5 stars 5.00 score 8 scripts
poissonconsulting
embr:Model Builder Utility Functions and Virtual Classes
Utility functions and virtual classes shared by model builder packages such as tmbr, jmbr and smbr.
Maintained by Joe Thorley. Last updated 2 months ago.
3 stars 4.61 score 4 scripts 3 dependents
c3s
businessPlanR:Simple Modelling Tools for Business Plans
A collection of S4 classes, methods and functions to create and visualize business plans. Different types of cash flows can be defined, which can then be used and tabulated to create profit and loss statements, cash flow plans, investment and depreciation schedules, loan amortization schedules, etc. The methods are designed to produce handsome tables in both PDF and HTML using 'RMarkdown' or 'Shiny'.
Maintained by Meik Michalke. Last updated 2 years ago.
3.70 score 2 scripts
mrchypark
elbird:Blazing Fast Morphological Analyzer Based on Kiwi(Korean Intelligent Word Identifier)
This is the R wrapper package Kiwi(Korean Intelligent Word Identifier), a blazing fast speed morphological analyzer for Korean. It supports configuration of user dictionary and detection of unregistered nouns based on frequency.
Maintained by Chanyub Park. Last updated 2 years ago.
analyzerhacktoberfesthacktoberfest2021morphologicalcpp
34 stars 3.23 score 9 scripts
inbo
n2kanalysis:Generic Functions to Analyse Data from the 'Natura 2000' Monitoring
All generic functions and classes for the analysis for the 'Natura 2000' monitoring. The classes contain all required data and definitions to fit the model without the need to access other sources. Potentially they might need access to one or more parent objects. An aggregation object might for example need the result of an imputation object. The actual definition of the analysis, using these generic function and classes, is defined in dedictated analysis R packages for every monitoring scheme. For example 'abvanalysis' and 'watervogelanalysis'.
Maintained by Thierry Onkelinx. Last updated 2 months ago.
1 stars 3.18 score 7 scripts
coalesce-lab
stansum:Bayesian Models for Aggregated Relational Data and Network Scale-Up Method
Interface to various precompiled Stan models for Aggregated Relational Data that estimate, among other things, network degrees. Includes models by Zheng et al (2006) <doi:10.1198/016214505000001168>, Maltiel et al (2015) <doi:10.1214/15-AOAS827>, Baum & Marsden (2023) <doi:10.1016/j.socnet.2023.02.001>.
Maintained by Michal Bojanowski. Last updated 12 months ago.
1.70 score 1 scripts