R-universe search: topic:panel-data

Showing 6 of total 6 results (show query)

sebkrantz

collapse:Advanced and Fast Data Transformation

A C/C++ based package for advanced data transformation and statistical computing in R that is extremely fast, class-agnostic, robust and programmer friendly. Core functionality includes a rich set of S3 generic grouped and weighted statistical functions for vectors, matrices and data frames, which provide efficient low-level vectorizations, OpenMP multithreading, and skip missing values by default. These are integrated with fast grouping and ordering algorithms (also callable from C), and efficient data manipulation functions. The package also provides a flexible and rigorous approach to time series and panel data in R. It further includes fast functions for common statistical procedures, detailed (grouped, weighted) summary statistics, powerful tools to work with nested data, fast data object conversions, functions for memory efficient R programming, and helpers to effectively deal with variable labels, attributes, and missing data. It is well integrated with base R classes, 'dplyr'/'tibble', 'data.table', 'sf', 'units', 'plm' (panel-series and data frames), and 'xts'/'zoo'.

Maintained by Sebastian Krantz. Last updated 7 days ago.

data-aggregation data-analysis data-manipulation data-processing data-science data-transformation econometrics high-performance panel-data scientific-computing statistics time-series weighted weights cpp openmp

672 stars 16.68 score 708 scripts 99 dependents

fastverse

fastverse:A Suite of High-Performance Packages for Statistics and Data Manipulation

Easy installation, loading and management, of high-performance packages for statistical computing and data manipulation in R. The core 'fastverse' consists of 4 packages: 'data.table', 'collapse', 'kit' and 'magrittr', that jointly only depend on 'Rcpp'. The 'fastverse' can be freely and permanently extended with additional packages, both globally or for individual projects. Separate package verses can also be created. Fast packages for many common tasks such as time series, dates and times, strings, spatial data, statistics, data serialization, larger-than-memory processing, and compilation of R code are listed in the README file: <https://github.com/fastverse/fastverse#suggested-extensions>.

Maintained by Sebastian Krantz. Last updated 1 months ago.

c cpp data-aggregation data-manipulation data-science data-transformation high-performance low-dependency panel-data statistical-computing time-series weights

266 stars 8.98 score 222 scripts

ropensci

dynamite:Bayesian Modeling and Causal Inference for Multivariate Longitudinal Data

Easy-to-use and efficient interface for Bayesian inference of complex panel (time series) data using dynamic multivariate panel models by Helske and Tikka (2024) <doi:10.1016/j.alcr.2024.100617>. The package supports joint modeling of multiple measurements per individual, time-varying and time-invariant effects, and a wide range of discrete and continuous distributions. Estimation of these dynamic multivariate panel models is carried out via 'Stan'. For an in-depth tutorial of the package, see (Tikka and Helske, 2024) <doi:10.48550/arXiv.2302.01607>.

Maintained by Santtu Tikka. Last updated 3 days ago.

bayesian-inference panel-data stan statistical-models

29 stars 7.90 score 20 scripts

floswald

psidR:Build Panel Data Sets from PSID Raw Data

Makes it easy to build panel data in wide format from Panel Survey of Income Dynamics (PSID) delivered raw data. Downloads data directly from the PSID server using the 'SAScii' package. 'psidR' takes care of merging data from each wave onto a cross-period index file, so that individuals can be followed over time. The user must specify which years they are interested in, and the 'PSID' variable names (e.g. ER21003) for each year (they differ in each year). The package offers helper functions to retrieve variable names from different waves. There are different panel data designs and sample subsetting criteria implemented ("SRC", "SEO", "immigrant" and "latino" samples). More information about the PSID can be obtained at <https://simba.isr.umich.edu/data/data.aspx>.

Maintained by Florian Oswald. Last updated 5 months ago.

dataset panel-data psid

54 stars 6.04 score 16 scripts

cadam00

poobly:Poolability Tests in Panel Data

Homogeneity tests of the coefficients in panel data. Currently, only the Hsiao test for determining coefficient homogeneity between the panel data individuals is implemented, as described in Hsiao (2022), "Analysis of Panel Data" (<doi:10.1017/9781009057745>).

Maintained by Christos Adam. Last updated 2 months ago.

homogeneity hsiao-test panel-data

1 stars 4.00 score

hujiebai

DPTM:Dynamic Panel Multiple Threshold Model with Fixed Effects

Compute the fixed effects dynamic panel threshold model suggested by Ramírez-Rondán (2020) <doi:10.1080/07474938.2019.1624401>, and dynamic panel linear model suggested by Hsiao et al. (2002) <doi:10.1016/S0304-4076(01)00143-9>, where maximum likelihood type estimators are used. Multiple thresholds estimation based on Markov Chain Monte Carlo (MCMC) is allowed, and model selection of linear model, threshold model and multiple threshold model is also allowed.

Maintained by Bai Hujie. Last updated 8 days ago.

dynamic panel-data thresholds cpp

2 stars 3.78 score