Showing 12 of total 12 results (show query)
vineetbansal
pyMTurkR:A Client for the 'MTurk' Requester API
Provides access to the latest 'Amazon Mechanical Turk' ('MTurk') <https://www.mturk.com> Requester API (version '2017–01–17'), replacing the now deprecated 'MTurkR' package.
Maintained by Vineet Bansal. Last updated 3 years ago.
16.2 match 3.78 score 7 scripts 1 dependents
thiyangt
DSjobtracker:What Skills and Qualifications are Required for Data Science Related Jobs?
Dataset containing information about job listings for data science job roles.
Maintained by Thiyanga S. Talagala. Last updated 1 years ago.
datasetqualificationsskillsstatisticstidy
12.9 match 3 stars 4.29 score 13 scripts
dbosak01
sassy:Makes 'R' Easier for Everyone
A meta-package that aims to make 'R' easier for everyone, especially programmers who have a background in 'SAS®' software. This set of packages brings many useful concepts to 'R', including data libraries, data dictionaries, formats and format catalogs, a data step, and a traceable log. The 'flagship' package is a reporting package that can output in text, rich text, 'PDF', 'HTML', and 'DOCX' file formats.
Maintained by David Bosak. Last updated 6 months ago.
3.8 match 21 stars 7.74 score 92 scripts
allenzhuaz
PPQplan:Process Performance Qualification (PPQ) Plans in Chemistry, Manufacturing and Controls (CMC) Statistical Analysis
Assessment for statistically-based PPQ sampling plan, including calculating the passing probability, optimizing the baseline and high performance cutoff points, visualizing the PPQ plan and power dynamically. The analytical idea is based on the simulation methods from the textbook Burdick, R. K., LeBlond, D. J., Pfahler, L. B., Quiroz, J., Sidor, L., Vukovinsky, K., & Zhang, L. (2017). Statistical Methods for CMC Applications. In Statistical Applications for Chemistry, Manufacturing and Controls (CMC) in the Pharmaceutical Industry (pp. 227-250). Springer, Cham.
Maintained by Yalin Zhu. Last updated 3 years ago.
biostatisticspharmaceuticalssampling-methods
5.5 match 1 stars 4.11 score 13 scripts
nlmixr2
rxode2:Facilities for Simulating from ODE-Based Models
Facilities for running simulations from ordinary differential equation ('ODE') models, such as pharmacometrics and other compartmental models. A compilation manager translates the ODE model into C, compiles it, and dynamically loads the object code into R for improved computational efficiency. An event table object facilitates the specification of complex dosing regimens (optional) and sampling schedules. NB: The use of this package requires both C and Fortran compilers, for details on their use with R please see Section 6.3, Appendix A, and Appendix D in the "R Administration and Installation" manual. Also the code is mostly released under GPL. The 'VODE' and 'LSODA' are in the public domain. The information is available in the inst/COPYRIGHTS.
Maintained by Matthew L. Fidler. Last updated 30 days ago.
1.6 match 40 stars 11.24 score 220 scripts 13 dependents
tidyverse
duckplyr:A 'DuckDB'-Backed Version of 'dplyr'
A drop-in replacement for 'dplyr', powered by 'DuckDB' for performance. Offers convenient utilities for working with in-memory and larger-than-memory data while retaining full 'dplyr' compatibility.
Maintained by Kirill Müller. Last updated 5 days ago.
analyticsdataframedplyrduckdbperformance
1.3 match 309 stars 11.33 score 220 scripts
jsilve24
fido:Bayesian Multinomial Logistic Normal Regression
Provides methods for fitting and inspection of Bayesian Multinomial Logistic Normal Models using MAP estimation and Laplace Approximation as developed in Silverman et. Al. (2022) <https://www.jmlr.org/papers/v23/19-882.html>. Key functionality is implemented in C++ for scalability. 'fido' replaces the previous package 'stray'.
Maintained by Justin Silverman. Last updated 18 days ago.
1.5 match 20 stars 8.31 score 103 scripts
cran
MGBT:Multiple Grubbs-Beck Low-Outlier Test
Compute the multiple Grubbs-Beck low-outlier test on positively distributed data and utilities for noninterpretive U.S. Geological Survey annual peak-streamflow data processing discussed in Cohn et al. (2013) <doi:10.1002/wrcr.20392> and England et al. (2017) <doi:10.3133/tm4B5>.
Maintained by William H. Asquith. Last updated 4 years ago.
5.1 match 1 stars 1.70 score 3 scriptscran
mvdalab:Multivariate Data Analysis Laboratory
An open-source implementation of latent variable methods and multivariate modeling tools. The focus is on exploratory analyses using dimensionality reduction methods including low dimensional embedding, classical multivariate statistical tools, and tools for enhanced interpretation of machine learning methods (i.e. intelligible models to provide important information for end-users). Target domains include extension to dedicated applications e.g. for manufacturing process modeling, spectroscopic analyses, and data mining.
Maintained by Nelson Lee Afanador. Last updated 2 years ago.
3.4 match 2.18 score 1 dependents
kjhealy
gssrdoc:Document General Social Survey Variable
The General Social Survey (GSS) is a long-running, mostly annual survey of US households. It is administered by the National Opinion Research Center (NORC). This package contains the a tibble with information on the survey variables, together with every variable documented as an R help page. For more information on the GSS see \url{http://gss.norc.org}.
Maintained by Kieran Healy. Last updated 11 months ago.
1.9 match 2.28 score 38 scripts
cmstatr
cmstatr:Statistical Methods for Composite Material Data
An implementation of the statistical methods commonly used for advanced composite materials in aerospace applications. This package focuses on calculating basis values (lower tolerance bounds) for material strength properties, as well as performing the associated diagnostic tests. This package provides functions for calculating basis values assuming several different distributions, as well as providing functions for non-parametric methods of computing basis values. Functions are also provided for testing the hypothesis that there is no difference between strength and modulus data from an alternate sample and that from a "qualification" or "baseline" sample. For a discussion of these statistical methods and their use, see the Composite Materials Handbook, Volume 1 (2012, ISBN: 978-0-7680-7811-4). Additional details about this package are available in the paper by Kloppenborg (2020, <doi:10.21105/joss.02265>).
Maintained by Stefan Kloppenborg. Last updated 4 months ago.
composite-material-datadatamaterials-sciencestatistical-analysisstatistics
0.5 match 4 stars 6.26 score 23 scripts