CRTFASTGEEPWR: A SAS Macro for Power of Generalized Estimating Equations...
Multi-period cluster randomized trials (CRTs) are increasingly used for the evaluation of interventions delivered at the group level. While generalized estimating equations (GEE) are commonly used to...
View ArticleHolistic Generalized Linear Models
Holistic linear regression extends the classical best subset selection problem by adding additional constraints designed to improve the model quality. These constraints include sparsity-inducing...
View ArticlePUMP: Estimating Power, Minimum Detectable Effect Size, and Sample Size When...
For randomized controlled trials (RCTs) with a single intervention's impact being measured on multiple outcomes, researchers often apply a multiple testing procedure (such as Bonferroni or...
View Articlemelt: Multiple Empirical Likelihood Tests in R
Empirical likelihood enables a nonparametric, likelihood-driven style of inference without relying on assumptions frequently made in parametric models. Empirical likelihood-based tests are...
View Articlegcimpute: A Package for Missing Data Imputation
This article introduces the Python package gcimpute for missing data imputation. Package gcimpute can impute missing data with many different variable types, including continuous, binary, ordinal,...
View ArticleDoubleML: An Object-Oriented Implementation of Double Machine Learning in R
The R package DoubleML implements the double/debiased machine learning framework of Chernozhukov, Chetverikov, Demirer, Duflo, Hansen, Newey, and Robins (2018). It provides functionalities to estimate...
View ArticleThe R Package markets: Estimation Methods for Markets in Equilibrium and...
Market models constitute a significant cornerstone of empirical applications in business, industrial organization, and policymaking macroeconomics. The econometric literature proposes various...
View ArticleThe R Package tipsae: Tools for Mapping Proportions and Indicators on the...
The tipsae package implements a set of small area estimation tools for mapping proportions and indicators defined on the unit interval. It provides for small area models defined at area level,...
View Articlesalmon: A Symbolic Linear Regression Package for Python
One of the most attractive features of R is its linear modeling capabilities. We describe a Python package, salmon, that brings the best of R's linear modeling functionality to Python in a Pythonic way...
View ArticleModeling Big, Heterogeneous, Non-Gaussian Spatial and Spatio-Temporal Data...
Non-Gaussian spatial and spatio-temporal data are becoming increasingly prevalent, and their analysis is needed in a variety of disciplines. FRK is an R package for spatial and spatio-temporal modeling...
View ArticleModeling Nonstationary Financial Volatility with the R Package tvgarch
Certain events can make the structure of volatility of financial returns to change, making it nonstationary. Models of time-varying conditional variance such as generalized autoregressive conditional...
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