Software (selected)

gmwmx: Generalized Method of Wavelet Moments with eXogenous inputs

The gmwmx R package implements 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.

navigation: Analyze the Impact of Sensor Error Modelling on Navigation Performance

The navigation package implements a framework to analyze the impact of sensor error modeling on performance of integrated navigation (sensor fusion) based on IMU, GPS, and barometer data introduced in Cucci et al. (2023).

simts: Time Series Analysis Tools

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: Wavelet Variance

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).

avar: Allan Variance

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).

idarps: Introduction to Data Analytics with R for Pharmaceutical Sciences

The idarps R package offers datasets and functions specifically designed for the "Modelling and Data Analysis for Pharmaceutical Sciences" course given at the University of Geneva in the M.Sc. of Pharmaceutical Sciences. These datasets are curated to showcase diverse methods of data analysis and statistical modeling, focusing on applications within the context of Health science. Additionally, the package includes a range of functions dedicated to data visualization.