Showing 14 of total 14 results (show query)
tidymodels
dials:Tools for Creating Tuning Parameter Values
Many models contain tuning parameters (i.e. parameters that cannot be directly estimated from the data). These tools can be used to define objects for creating, simulating, or validating values for such parameters.
Maintained by Hannah Frick. Last updated 1 months ago.
114 stars 14.31 score 426 scripts 52 dependents
crunch-io
crunch:Crunch.io Data Tools
The Crunch.io service <https://crunch.io/> provides a cloud-based data store and analytic engine, as well as an intuitive web interface. Using this package, analysts can interact with and manipulate Crunch datasets from within R. Importantly, this allows technical researchers to collaborate naturally with team members, managers, and clients who prefer a point-and-click interface.
Maintained by Greg Freedman Ellis. Last updated 8 days ago.
9 stars 10.47 score 200 scripts 2 dependents
trinker
qdap:Bridging the Gap Between Qualitative Data and Quantitative Analysis
Automates many of the tasks associated with quantitative discourse analysis of transcripts containing discourse including frequency counts of sentence types, words, sentences, turns of talk, syllables and other assorted analysis tasks. The package provides parsing tools for preparing transcript data. Many functions enable the user to aggregate data by any number of grouping variables, providing analysis and seamless integration with other R packages that undertake higher level analysis and visualization of text. This affords the user a more efficient and targeted analysis. 'qdap' is designed for transcript analysis, however, many functions are applicable to other areas of Text Mining/ Natural Language Processing.
Maintained by Tyler Rinker. Last updated 5 years ago.
qdapquantitative-discourse-analysistext-analysistext-miningtext-plottingopenjdk
176 stars 9.61 score 1.3k scripts 3 dependents
myles-lewis
nestedcv:Nested Cross-Validation with 'glmnet' and 'caret'
Implements nested k*l-fold cross-validation for lasso and elastic-net regularised linear models via the 'glmnet' package and other machine learning models via the 'caret' package <doi:10.1093/bioadv/vbad048>. Cross-validation of 'glmnet' alpha mixing parameter and embedded fast filter functions for feature selection are provided. Described as double cross-validation by Stone (1977) <doi:10.1111/j.2517-6161.1977.tb01603.x>. Also implemented is a method using outer CV to measure unbiased model performance metrics when fitting Bayesian linear and logistic regression shrinkage models using the horseshoe prior over parameters to encourage a sparse model as described by Piironen & Vehtari (2017) <doi:10.1214/17-EJS1337SI>.
Maintained by Myles Lewis. Last updated 9 days ago.
12 stars 7.90 score 46 scripts
dgerlanc
portfolio:Analysing Equity Portfolios
Classes for analysing and implementing equity portfolios, including routines for generating tradelists and calculating exposures to user-specified risk factors.
Maintained by Daniel Gerlanc. Last updated 7 months ago.
financeportfolio-constructionrisk-modelling
16 stars 6.71 score 106 scripts
shaunpwilkinson
aphid:Analysis with Profile Hidden Markov Models
Designed for the development and application of hidden Markov models and profile HMMs for biological sequence analysis. Contains functions for multiple and pairwise sequence alignment, model construction and parameter optimization, file import/export, implementation of the forward, backward and Viterbi algorithms for conditional sequence probabilities, tree-based sequence weighting, and sequence simulation. Features a wide variety of potential applications including database searching, gene-finding and annotation, phylogenetic analysis and sequence classification. Based on the models and algorithms described in Durbin et al (1998, ISBN: 9780521629713).
Maintained by Shaun Wilkinson. Last updated 9 months ago.
22 stars 6.58 score 38 scripts 3 dependents
gitter-lab
LPWC:Lag Penalized Weighted Correlation for Time Series Clustering
Computes a time series distance measure for clustering based on weighted correlation and introduction of lags. The lags capture delayed responses in a time series dataset. The timepoints must be specified. T. Chandereng, A. Gitter (2020) <doi:10.1186/s12859-019-3324-1>.
Maintained by Thevaa Chandereng. Last updated 5 years ago.
bioinformaticsclusteringtime-series
20 stars 5.23 score 17 scripts
r-forge
RobAStBase:Robust Asymptotic Statistics
Base S4-classes and functions for robust asymptotic statistics.
Maintained by Matthias Kohl. Last updated 2 months ago.
4.96 score 64 scripts 4 dependents
philmikejones
rakeR:Easy Spatial Microsimulation (Raking) in R
Functions for performing spatial microsimulation ('raking') in R.
Maintained by Phil Mike Jones. Last updated 6 years ago.
ipfrakerrakingspatial-microsimulation
11 stars 3.74 score 8 scripts
johnrstevens
phyext2:An Extension (for Package 'SigTree') of Some of the Classes in Package 'phylobase'
Based on (but not identical to) the no-longer-maintained package 'phyext', provides enhancements to 'phylobase' classes, specifically for use by package 'SigTree'; provides classes and methods which help users manipulate branch-annotated trees (as in 'SigTree'); also provides support for a few other extra features.
Maintained by John R. Stevens. Last updated 10 years ago.
1.48 score 8 scripts 1 dependents
chiranjibsbioinfo
EGRNi:Ensemble Gene Regulatory Network Inference
Gene regulatory network constructed using combined score obtained from individual network inference method. The combined score measures the significance of edges in the ensemble network. Fisher's weighted method has been implemented to combine the outcomes of different methods based on the probability values. The combined score follows chi-square distribution with 2n degrees of freedom. <doi:10.22271/09746315.2020.v16.i3.1358>.
Maintained by Chiranjib Sarkar. Last updated 2 years ago.
1.18 score 15 scripts
yuande
signatureSurvival:Signature Survival Analysis
When multiple Cox proportional hazard models are performed on clinical data (month or year and status) and a set of differential expressions of genes, the results (Hazard risks, z-scores and p-values) can be used to create gene-expression signatures. Weights are calculated using the survival p-values of genes and are utilized to calculate expression values of the signature across the selected genes in all patients in a cohort. A Single or multiple univariate or multivariate Cox proportional hazard survival analyses of the patients in one cohort can be performed by using the gene-expression signature and visualized using our survival plots.
Maintained by Yuan-De Tan. Last updated 2 years ago.
1 stars 1.00 score