Smoothing splines with penalties on order m derivatives.

Performs demographic, bifurcation and evolutionary analysis of physiologically structured population models, which is a class of models that consistently translates continuous-time models of individual life history to the population level.
    A model of individual life history has to be implemented specifying the individual-level functions that determine the life history, such as development and mortality rates and fecundity. 
    M.A. Kirkilionis, O. Diekmann, B. Lisser, M. Nool, B. Sommeijer & A.M. de Roos (2001) <doi:10.1142/S0218202501001264>.
    O.Diekmann, M.Gyllenberg & J.A.J.Metz (2003) <doi:10.1016/S0040-5809(02)00058-8>.
    A.M. de Roos (2008) <doi:10.1111/j.1461-0248.2007.01121.x>.

Sample size calculations in causal inference with observational data are increasingly desired. This package is a tool to calculate sample size under prespecified power with minimal summary quantities needed.

Provides quasi-Newton methods to minimize partially separable
    functions. The methods are largely described by  
    Nocedal and Wright (2006) <doi:10.1007/978-0-387-40065-5>.

Includes functions and data used in the book "Presenting Statistical Results Effectively", Andersen and Armstrong (2022, ISBN: 978-1446269800).  Several functions aid in data visualization - creating compact letter displays for simple slopes, kernel density estimates with normal density overlay.  Other functions aid in post-model evaluation heatmap fit statistics for binary predictors, several variable importance measures, compact letter displays and simple-slope calculation. Finally, the package makes available the example datasets used in the book.

Calculate Plant Stress Response Index (PSRI) from time-series
    germination data with optional radicle vigor integration. Built on the
    methodological foundation of the Osmotic Stress Response Index (OSRI)
    framework developed by Walne et al. (2020) <doi:10.1002/agg2.20087>.
    Provides clean, direct PSRI calculations suitable for agricultural research
    and statistical analysis. Note: This package implements methodology
    currently under peer review. Please contact the author before publication
    using this approach.