Software (selected)


The proportion estimation with marginal proxy information (pempi) package, allows to estimate and build confidence intervals for proportions, from random or stratified samples and census data with participation bias. Measurement errors in the form of false positive and false negative are also included in the inferential procedure. The pempi package also contains code for simulation studies and sensitivity analysis reported in the companion paper Guerrier et al. (2024) , as well as the Austrian dataset on COVID-19 prevalence in November 2020.

simts is an R package that contains various tools for time series analysis. Indeed, this R package provides a series of tools to simulate, plot, estimate, select and forecast different time series models. In particular, it incorporates a technique called Generalized Method of Wavelet Moments (GMWM) as well as its robust implementation for fast and robust parameter estimation of time series models which is described, for example, in Guerrier et al. (2013). This R package is originally conceived as a support to the online textbook "Applied Time Series Analysis with R".

wv is an R package that provides a series of tools to compute and plot quantities related to classical and robust wavelet variance for time series and regular lattices. More details can be found, for example, in Serroukh et al. (2000) and Guerrier et al. (2021).

gmwmx is an R package that implement the Generalized Method of Wavelet Moments with Exogenous Inputs estimator (GMWMX) introduced in Cucci et al. (2022). This statistical framework allows to estimate complex times series models in a computationally efficient way.

avar is an R package that implements the Allan variance and Allan variance linear regression estimator for latent time series models. More details can be found, for example, in Guerrier et al. (2016).

gmwm is an R package that implements the classical and robust Generalized Method of Wavelet Moments estimator. More details can be found in Guerrier et al. (2013) and Guerrier et al. (2021).