Browse Items (8208 total)

Despite the huge availability of software to estimate cross-sectional spatial models,
there are only few functions to estimate models dealing with spatial limited dependent
variable. This paper fills this gap introducing the new R package spldv.…

We develop an R package panelView and a Stata package panelview for panel data
visualization. They are designed to assist causal analysis with panel data and have three
main functionalities: (1) They plot the treatment status and missing values in…

The issue of variance components testing arises naturally when building mixed-effects
models, to decide which effects should be modeled as fixed or random or to build parsimonious models. While tests for fixed effects are available in R for models…

This paper introduces ARCHModels.jl, a package for the Julia programming language
that implements a number of univariate and multivariate autoregressive conditional heteroskedasticity models. This model class is the workhorse tool for modeling the…

DataFrames.jl is a package written for and in the Julia language offering flexible and
efficient handling of tabular data sets in memory. Thanks to Julia’s unique strengths, it
provides an appealing set of features: Rich support for standard data…

Endogeneity is a common problem in any causal analysis. It arises when the independence assumption between an explanatory variable and the error in a statistical model is
violated. The causes of endogeneity are manifold and include response bias in…

Covariate-adaptive randomization is gaining popularity in clinical trials because they
enable the generation of balanced allocations with respect to covariates. Over the past
decade, substantial progress has been made in both new innovative…

The growth of populations is of interest in a broad variety of fields, such as epidemiology, economics or biology. Although a large variety of growth models are available in
the scientific literature, their application usually requires advanced…

Unit root tests form an essential part of any time series analysis. We provide practitioners with a single, unified framework for comprehensive and reliable unit root testing
in the R package bootUR. The package’s backbone is the popular augmented…

Disaggregation modeling, or downscaling, has become an important discipline in epidemiology. Surveillance data, aggregated over large regions, is becoming more common,
leading to an increasing demand for modeling frameworks that can deal with this…