Showing 6 of total 6 results (show query)
tidymodels
infer:Tidy Statistical Inference
The objective of this package is to perform inference using an expressive statistical grammar that coheres with the tidy design framework.
Maintained by Simon Couch. Last updated 6 months ago.
736 stars 15.75 score 3.5k scripts 18 dependents
r-lib
generics:Common S3 Generics not Provided by Base R Methods Related to Model Fitting
In order to reduce potential package dependencies and conflicts, generics provides a number of commonly used S3 generics.
Maintained by Hadley Wickham. Last updated 1 years ago.
61 stars 14.00 score 131 scripts 9.8k dependents
statisfactions
simpr:Flexible 'Tidyverse'-Friendly Simulations
A general, 'tidyverse'-friendly framework for simulation studies, design analysis, and power analysis. Specify data generation, define varying parameters, generate data, fit models, and tidy model results in a single pipeline, without needing loops or custom functions.
Maintained by Ethan Brown. Last updated 9 months ago.
43 stars 6.89 score 30 scripts
silvaneojunior
kDGLM:Bayesian Analysis of Dynamic Generalized Linear Models
Provide routines for filtering and smoothing, forecasting, sampling and Bayesian analysis of Dynamic Generalized Linear Models using the methodology described in Alves et al. (2024)<doi:10.48550/arXiv.2201.05387> and dos Santos Jr. et al. (2024)<doi:10.48550/arXiv.2403.13069>.
Maintained by Silvaneo dos Santos Jr.. Last updated 13 days ago.
2 stars 5.70 score 9 scripts
bergsmat
spec:A Data Specification Format and Interface
Creates a data specification that describes the columns of a table (data.frame). Provides methods to read, write, and update the specification. Checks whether a table matches its specification. See specification.data.frame(),read.spec(), write.spec(), as.csv.spec(), respecify.character(), and %matches%.data.frame().
Maintained by Tim Bergsma. Last updated 1 years ago.
1 stars 3.98 score 160 scripts 1 dependents
georgeweigt
itsmr:Time Series Analysis Using the Innovations Algorithm
Provides functions for modeling and forecasting time series data. Forecasting is based on the innovations algorithm. A description of the innovations algorithm can be found in the textbook "Introduction to Time Series and Forecasting" by Peter J. Brockwell and Richard A. Davis. <https://link.springer.com/book/10.1007/b97391>.
Maintained by George Weigt. Last updated 3 years ago.
2.34 score 218 scripts