Showing 200 of total 1489 results (show query)

insightsengineering

teal.reporter:Reporting Tools for 'shiny' Modules

Prebuilt 'shiny' modules containing tools for the generation of 'rmarkdown' reports, supporting reproducible research and analysis.

Maintained by Dawid Kaledkowski. Last updated 2 months ago.

nestreportingshiny

88.2 match 8 stars 9.34 score 19 scripts 6 dependents

pik-piam

remind2:The REMIND R package (2nd generation)

Contains the REMIND-specific routines for data and model output manipulation.

Maintained by Renato Rodrigues. Last updated 6 days ago.

53.4 match 8.88 score 161 scripts 5 dependents

pik-piam

limes:The liMES R package

Contains the LIMES-specific routines for data and model output manipulation.

Maintained by Sebastian Osorio. Last updated 8 days ago.

73.9 match 1 stars 4.60 score 5 scripts

bioc

systemPipeR:systemPipeR: Workflow Environment for Data Analysis and Report Generation

systemPipeR is a multipurpose data analysis workflow environment that unifies R with command-line tools. It enables scientists to analyze many types of large- or small-scale data on local or distributed computer systems with a high level of reproducibility, scalability and portability. At its core is a command-line interface (CLI) that adopts the Common Workflow Language (CWL). This design allows users to choose for each analysis step the optimal R or command-line software. It supports both end-to-end and partial execution of workflows with built-in restart functionalities. Efficient management of complex analysis tasks is accomplished by a flexible workflow control container class. Handling of large numbers of input samples and experimental designs is facilitated by consistent sample annotation mechanisms. As a multi-purpose workflow toolkit, systemPipeR enables users to run existing workflows, customize them or design entirely new ones while taking advantage of widely adopted data structures within the Bioconductor ecosystem. Another important core functionality is the generation of reproducible scientific analysis and technical reports. For result interpretation, systemPipeR offers a wide range of plotting functionality, while an associated Shiny App offers many useful functionalities for interactive result exploration. The vignettes linked from this page include (1) a general introduction, (2) a description of technical details, and (3) a collection of workflow templates.

Maintained by Thomas Girke. Last updated 5 months ago.

geneticsinfrastructuredataimportsequencingrnaseqriboseqchipseqmethylseqsnpgeneexpressioncoveragegenesetenrichmentalignmentqualitycontrolimmunooncologyreportwritingworkflowstepworkflowmanagement

19.8 match 53 stars 11.56 score 344 scripts 3 dependents

alanarnholt

BSDA:Basic Statistics and Data Analysis

Data sets for book "Basic Statistics and Data Analysis" by Larry J. Kitchens.

Maintained by Alan T. Arnholt. Last updated 2 years ago.

24.1 match 7 stars 9.11 score 1.3k scripts 6 dependents

pheymanss

chronicle:Grammar for Creating R Markdown Reports

A system for creating R Markdown reports with a sequential syntax.

Maintained by Philippe Heymans Smith. Last updated 1 years ago.

36.1 match 29 stars 5.54 score 24 scripts

rmi-pacta

pacta.portfolio.report:pacta.portfolio.report

For more information visit <https://rmi.org/>.

Maintained by Monika Furdyna. Last updated 2 months ago.

climate-changesustainable-finance

42.3 match 1 stars 4.10 score 2 scripts 1 dependents

framverse

framrsquared:FRAM Database Interface

A convenient tool for interfacing with FRAM access databases in R environments.

Maintained by Ty Garber. Last updated 2 months ago.

19.7 match 6 stars 5.06 score 9 scripts

bioc

Biobase:Biobase: Base functions for Bioconductor

Functions that are needed by many other packages or which replace R functions.

Maintained by Bioconductor Package Maintainer. Last updated 5 months ago.

infrastructurebioconductor-packagecore-package

5.5 match 9 stars 16.45 score 6.6k scripts 1.8k dependents

inbo

INBOmd:Markdown Templates for INBO

Several templates to generate reports, presentations and posters.

Maintained by Thierry Onkelinx. Last updated 1 years ago.

bookdownrmarkdownxelatex

17.4 match 12 stars 4.52 score 11 scripts

rstudio

rstudioapi:Safely Access the RStudio API

Access the RStudio API (if available) and provide informative error messages when it's not.

Maintained by Kevin Ushey. Last updated 4 months ago.

3.6 match 172 stars 18.81 score 3.6k scripts 2.1k dependents

thiyangt

denguedatahub:A Tidy Format Datasets of Dengue by Country

Provides a weekly, monthly, yearly summary of dengue cases by state/ province/ country.

Maintained by Thiyanga S. Talagala. Last updated 1 months ago.

openjdk

12.8 match 11 stars 5.12 score 34 scripts

hdvinod

generalCorr:Generalized Correlations, Causal Paths and Portfolio Selection

Function gmcmtx0() computes a more reliable (general) correlation matrix. Since causal paths from data are important for all sciences, the package provides many sophisticated functions. causeSummBlk() and causeSum2Blk() give easy-to-interpret causal paths. Let Z denote control variables and compare two flipped kernel regressions: X=f(Y, Z)+e1 and Y=g(X, Z)+e2. Our criterion Cr1 says that if |e1*Y|>|e2*X| then variation in X is more "exogenous or independent" than in Y, and the causal path is X to Y. Criterion Cr2 requires |e2|<|e1|. These inequalities between many absolute values are quantified by four orders of stochastic dominance. Our third criterion Cr3, for the causal path X to Y, requires new generalized partial correlations to satisfy |r*(x|y,z)|< |r*(y|x,z)|. The function parcorVec() reports generalized partials between the first variable and all others. The package provides several R functions including get0outliers() for outlier detection, bigfp() for numerical integration by the trapezoidal rule, stochdom2() for stochastic dominance, pillar3D() for 3D charts, canonRho() for generalized canonical correlations, depMeas() measures nonlinear dependence, and causeSummary(mtx) reports summary of causal paths among matrix columns. Portfolio selection: decileVote(), momentVote(), dif4mtx(), exactSdMtx() can rank several stocks. Functions whose names begin with 'boot' provide bootstrap statistical inference, including a new bootGcRsq() test for "Granger-causality" allowing nonlinear relations. A new tool for evaluation of out-of-sample portfolio performance is outOFsamp(). Panel data implementation is now included. See eight vignettes of the package for theory, examples, and usage tips. See Vinod (2019) \doi{10.1080/03610918.2015.1122048}.

Maintained by H. D. Vinod. Last updated 1 years ago.

13.7 match 2 stars 4.48 score 63 scripts 1 dependents

r-forge

surveillance:Temporal and Spatio-Temporal Modeling and Monitoring of Epidemic Phenomena

Statistical methods for the modeling and monitoring of time series of counts, proportions and categorical data, as well as for the modeling of continuous-time point processes of epidemic phenomena. The monitoring methods focus on aberration detection in count data time series from public health surveillance of communicable diseases, but applications could just as well originate from environmetrics, reliability engineering, econometrics, or social sciences. The package implements many typical outbreak detection procedures such as the (improved) Farrington algorithm, or the negative binomial GLR-CUSUM method of Hoehle and Paul (2008) <doi:10.1016/j.csda.2008.02.015>. A novel CUSUM approach combining logistic and multinomial logistic modeling is also included. The package contains several real-world data sets, the ability to simulate outbreak data, and to visualize the results of the monitoring in a temporal, spatial or spatio-temporal fashion. A recent overview of the available monitoring procedures is given by Salmon et al. (2016) <doi:10.18637/jss.v070.i10>. For the retrospective analysis of epidemic spread, the package provides three endemic-epidemic modeling frameworks with tools for visualization, likelihood inference, and simulation. hhh4() estimates models for (multivariate) count time series following Paul and Held (2011) <doi:10.1002/sim.4177> and Meyer and Held (2014) <doi:10.1214/14-AOAS743>. twinSIR() models the susceptible-infectious-recovered (SIR) event history of a fixed population, e.g, epidemics across farms or networks, as a multivariate point process as proposed by Hoehle (2009) <doi:10.1002/bimj.200900050>. twinstim() estimates self-exciting point process models for a spatio-temporal point pattern of infective events, e.g., time-stamped geo-referenced surveillance data, as proposed by Meyer et al. (2012) <doi:10.1111/j.1541-0420.2011.01684.x>. A recent overview of the implemented space-time modeling frameworks for epidemic phenomena is given by Meyer et al. (2017) <doi:10.18637/jss.v077.i11>.

Maintained by Sebastian Meyer. Last updated 1 days ago.

cpp

5.1 match 2 stars 10.68 score 446 scripts 3 dependents

pik-piam

mrremind:MadRat REMIND Input Data Package

The mrremind packages contains data preprocessing for the REMIND model.

Maintained by Lavinia Baumstark. Last updated 3 days ago.

8.5 match 4 stars 6.25 score 15 scripts 1 dependents

cran

mistr:Mixture and Composite Distributions

A flexible computational framework for mixture distributions with the focus on the composite models.

Maintained by Lukas Sablica. Last updated 2 years ago.

12.3 match 4.28 score 80 scripts 4 dependents

johncoene

waiter:Loading Screen for 'Shiny'

Full screen and partial loading screens for 'Shiny' with spinners, progress bars, and notifications.

Maintained by John Coene. Last updated 11 months ago.

hacktoberfestshiny

4.0 match 496 stars 12.87 score 702 scripts 68 dependents

ankane

rollbar:Error Tracking and Logging

Reports errors and messages to Rollbar, the error tracking platform <https://rollbar.com>.

Maintained by Andrew Kane. Last updated 10 months ago.

13.3 match 12 stars 3.82 score 11 scripts