The Markowitz criterion is a multicriteria decision-making method that stands out in risk and uncertainty analysis in contexts where probabilities are known. This approach represents an evolution of Pascal's criterion by incorporating the dimension of variability. In this framework, the expected value reflects the anticipated return, while the standard deviation serves as a measure of risk. The 'markowitz' package provides a practical and accessible tool for implementing this method, enabling researchers and professionals to perform analyses without complex calculations. Thus, the package facilitates the application of the Markowitz criterion. More details on the method can be found in Octave Jokung-Nguéna (2001, ISBN 2100055372).

A collection of tools for analyzing significance of 
    Markowitz portfolios, using the delta method on the second moment
    matrix, <arxiv:1312.0557>.

Functions of marginal mean and quantile regression models are used to analyze environmental exposure and biomonitoring data with repeated measurements and non-detects, as well as longitudinal exposure data that include non-detects and time-dependent covariates.

Import xyz data from the NOAA (National Oceanic and Atmospheric Administration, <https://www.noaa.gov>), GEBCO (General Bathymetric Chart of the Oceans, <https://www.gebco.net>) and other sources, plot xyz data to prepare publication-ready figures, analyze xyz data to extract transects, get depth / altitude based on geographical coordinates, or calculate z-constrained least-cost paths.

It contains the function to apply MARMoT balancing technique discussed in: Silan, Boccuzzo, Arpino (2021) <DOI:10.1002/sim.9192>, Silan, Belloni, Boccuzzo, (2023) <DOI:10.1007/s10260-023-00695-0>; 
             furthermore it contains a function for computing the Deloof's approximation of the average rank 
             (and also a parallelized version) and a function to compute the Absolute Standardized Bias.

To implement a model-averaging approach with different renewal
    models, with a primary focus on forecasting large earthquakes. Based on
    six renewal models (i.e., Poisson, Gamma, Log-Logistics, Weibull,
    Log-Normal and BPT), model-averaged point estimates are calculated using
    AIC (or BIC) weights. Additionally, both percentile and studentized
    bootstrapped model-averaged confidence intervals are constructed. In
    comparison, point and interval estimation from the individual or "best"
    model (determined via model selection) can be retrieved.