EM algorithm for estimation of parameters and other methods in a quantile regression.

The goal of the package 'aldvmm' is to fit adjusted limited 
    dependent variable mixture models of health state utilities. Adjusted 
    limited dependent variable mixture models are finite mixtures of normal 
    distributions with an accumulation of density mass at the limits, and a gap 
    between 100% quality of life and the next smaller utility value. The 
    package 'aldvmm' uses the likelihood and expected value functions proposed 
    by Hernandez Alava and Wailoo (2015) <doi:10.1177/1536867X1501500307> using 
    normal component distributions and a multinomial logit model of 
    probabilities of component membership.

Accumulated Local Effects (ALE) were initially developed as a model-agnostic approach for global explanations of the results of black-box machine learning algorithms. ALE has a key advantage over other approaches like partial dependency plots (PDP) and SHapley Additive exPlanations (SHAP): its values represent a clean functional decomposition of the model. As such, ALE values are not affected by the presence or absence of interactions among variables in a mode. Moreover, its computation is relatively rapid. This package reimplements the algorithms for calculating ALE data and develops highly interpretable visualizations for plotting these ALE values. It also extends the original ALE concept to add bootstrap-based confidence intervals and ALE-based statistics that can be used for statistical inference. For more details, see Okoli, Chitu. 2023. “Statistical Inference Using Machine Learning and Classical Techniques Based on Accumulated Local Effects (ALE).” arXiv. <doi:10.48550/arXiv.2310.09877>.

An implementation of the ALFAM2 dynamic emission model for ammonia volatilization from field-applied animal slurry (manure with dry matter below about 15%). The model can be used to predict cumulative emission and emission rate of ammonia following field application of slurry. Predictions may be useful for emission inventory calculations, fertilizer management, assessment of mitigation strategies, or research aimed at understanding ammonia emission. Default parameter sets include effects of application method, slurry composition, and weather. The model structure is based on a simplified representation of the physical-chemical slurry-soil-atmosphere system. More information is available via citation("ALFAM2").