R-universe search: exports:opts

Showing 14 of total 14 results (show query)

rstudio

packrat:A Dependency Management System for Projects and their R Package Dependencies

Manage the R packages your project depends on in an isolated, portable, and reproducible way.

Maintained by Aron Atkins. Last updated 2 months ago.

406 stars 12.15 score 256 scripts 9 dependents

mlr-org

bbotk:Black-Box Optimization Toolkit

Features highly configurable search spaces via the 'paradox' package and optimizes every user-defined objective function. The package includes several optimization algorithms e.g. Random Search, Iterated Racing, Bayesian Optimization (in 'mlr3mbo') and Hyperband (in 'mlr3hyperband'). bbotk is the base package of 'mlr3tuning', 'mlr3fselect' and 'miesmuschel'.

Maintained by Marc Becker. Last updated 4 months ago.

bbotk black-box-optimization data-science hyperparameter-optimization hyperparameter-tuning machine-learning mlr3 optimization

22 stars 9.83 score 166 scripts 14 dependents

dgkf

options:Simple, Consistent Package Options

Simple mechanisms for defining and interpreting package options. Provides helpers for interpreting environment variables, global options, defining default values and more.

Maintained by Doug Kelkhoff. Last updated 1 days ago.

7.14 score 1.2k scripts

juba

obsplot:Create Charts with 'Observable Plot'

Creation of charts with the 'Observable Plot' 'JavaScript' library.

Maintained by Julien Barnier. Last updated 2 years ago.

60 stars 5.08 score 10 scripts

cran

preregr:Specify (Pre)Registrations and Export Them Human- And Machine-Readably

Preregistrations, or more generally, registrations, enable explicit timestamped and (often but not necessarily publicly) frozen documentation of plans and expectations as well as decisions and justifications. In research, preregistrations are commonly used to clearly document plans and facilitate justifications of deviations from those plans, as well as decreasing the effects of publication bias by enabling identification of research that was conducted but not published. Like reporting guidelines, (pre)registration forms often have specific structures that facilitate systematic reporting of important items. The 'preregr' package facilitates specifying (pre)registrations in R and exporting them to a human-readable format (using R Markdown partials or exporting to an 'HTML' file) as well as human-readable embedded data (using 'JSON'), as well as importing such exported (pre)registration specifications from such embedded 'JSON'.

Maintained by Gjalt-Jorn Peters. Last updated 2 years ago.

3.98 score

cranhaven

rock:Reproducible Open Coding Kit

The Reproducible Open Coding Kit ('ROCK', and this package, 'rock') was developed to facilitate reproducible and open coding, specifically geared towards qualitative research methods. Although it is a general-purpose toolkit, three specific applications have been implemented, specifically an interface to the 'rENA' package that implements Epistemic Network Analysis ('ENA'), means to process notes from Cognitive Interviews ('CIs'), and means to work with decentralized construct taxonomies ('DCTs'). The 'ROCK' and this 'rock' package are described in the ROCK book <https://rockbook.org> and more information, such as tutorials, is available at <https://rock.science>.

Maintained by Gjalt-Jorn Peters. Last updated 21 days ago.

archived packages r-universe

5 stars 3.40 score

cran

behaviorchange:Tools for Behavior Change Researchers and Professionals

Contains specialised analyses and visualisation tools for behavior change science. These facilitate conducting determinant studies (for example, using confidence interval-based estimation of relevance, CIBER, or CIBERlite plots, see Crutzen, Noijen & Peters (2017) <doi:10/ghtfz9>), systematically developing, reporting, and analysing interventions (for example, using Acyclic Behavior Change Diagrams), and reporting about intervention effectiveness (for example, using the Numbers Needed for Change, see Gruijters & Peters (2017) <doi:10/jzkt>), and computing the required sample size (using the Meaningful Change Definition, see Gruijters & Peters (2020) <doi:10/ghpnx8>). This package is especially useful for researchers in the field of behavior change or health psychology and to behavior change professionals such as intervention developers and prevention workers.

Maintained by Gjalt-Jorn Peters. Last updated 2 years ago.

3.40 score

cran

justifier:Human and Machine-Readable Justifications and Justified Decisions Based on 'YAML'

Leverages the 'yum' package to implement a 'YAML' ('YAML Ain't Markup Language', a human friendly standard for data serialization; see <https:yaml.org>) standard for documenting justifications, such as for decisions taken during the planning, execution and analysis of a study or during the development of a behavior change intervention as illustrated by Marques & Peters (2019) <doi:10.17605/osf.io/ndxha>. These justifications are both human- and machine-readable, facilitating efficient extraction and organisation.

Maintained by Gjalt-Jorn Peters. Last updated 2 years ago.

3.18 score

matherion

limonaid:Working with 'LimeSurvey' Surveys and Responses

'LimeSurvey' is Free/Libre Open Source Software for the development and administrations of online studies, using sophisticated tailoring capabilities to support multiple study designs (see <https://www.limesurvey.org>). This package supports programmatic creation of surveys that can then be imported into 'LimeSurvey', as well as user friendly import of responses from 'LimeSurvey' studies.

Maintained by Gjalt-Jorn Peters. Last updated 2 months ago.

3.00 score 6 scripts

cran

ufs:A Collection of Utilities

This is a new version of the 'userfriendlyscience' package, which has grown a bit unwieldy. Therefore, distinct functionalities are being 'consciously uncoupled' into different packages. This package contains the general-purpose tools and utilities (see the 'behaviorchange' package, the 'rosetta' package, and the soon-to-be-released 'scd' package for other functionality), and is the most direct 'successor' of the original 'userfriendlyscience' package. For example, this package contains a number of basic functions to create higher level plots, such as diamond plots, to easily plot sampling distributions, to generate confidence intervals, to plan study sample sizes for confidence intervals, and to do some basic operations such as (dis)attenuate effect size estimates.

Maintained by Gjalt-Jorn Peters. Last updated 1 years ago.

2.95 score 3 dependents

cran

rosetta:Parallel Use of Statistical Packages in Teaching

When teaching statistics, it can often be desirable to uncouple the content from specific software packages. To ease such efforts, the Rosetta Stats website (<https://rosettastats.com>) allows comparing analyses in different packages. This package is the companion to the Rosetta Stats website, aiming to provide functions that produce output that is similar to output from other statistical packages, thereby facilitating 'software-agnostic' teaching of statistics.

Maintained by Gjalt-Jorn Peters. Last updated 2 years ago.

2.70 score

cran

psyverse:Decentralized Unequivocality in Psychological Science

The constructs used to study the human psychology have many definitions and corresponding instructions for eliciting and coding qualitative data pertaining to constructs' content and for measuring the constructs. This plethora of definitions and instructions necessitates unequivocal reference to specific definitions and instructions in empirical and secondary research. This package implements a human- and machine-readable standard for specifying construct definitions and instructions for measurement and qualitative research based on 'YAML'. This standard facilitates systematic unequivocal reference to specific construct definitions and corresponding instructions in a decentralized manner (i.e. without requiring central curation; Peters (2020) <doi:10.31234/osf.io/xebhn>).

Maintained by Gjalt-Jorn Peters. Last updated 2 years ago.

2.70 score

capanum

STOPES:Selection Threshold Optimized Empirically via Splitting

Implements variable selection procedures for low to moderate size generalized linear regressions models. It includes the STOPES functions for linear regression (Capanu M, Giurcanu M, Begg C, Gonen M, Optimized variable selection via repeated data splitting, Statistics in Medicine, 2020, 19(6):2167-2184) as well as subsampling based optimization methods for generalized linear regression models (Marinela Capanu, Mihai Giurcanu, Colin B Begg, Mithat Gonen, Subsampling based variable selection for generalized linear models).

Maintained by Marinela Capanu. Last updated 3 years ago.

1.00 score

cran

OPTS:Optimization via Subsampling (OPTS)

Subsampling based variable selection for low dimensional generalized linear models. The methods repeatedly subsample the data minimizing an information criterion (AIC/BIC) over a sequence of nested models for each subsample. Marinela Capanu, Mihai Giurcanu, Colin B Begg, Mithat Gonen, Subsampling based variable selection for generalized linear models.

Maintained by Mihai Giurcanu. Last updated 3 years ago.

1.00 score