Provides functions to compute tree crown volume and projected area using
    geometric solid approximations (ellipsoid, cone, cylinder, paraboloid, and fan shapes),
    and to calculate morphometric indices commonly used in forest inventory and silviculture,
    including crown ratio, crown form factor, slenderness, salience index, and scope index.
    Methods are based on peer-reviewed literature in forest science.

Auto, Cross and Multi-dimensional recurrence quantification analysis. 
    Different methods for computing recurrence, cross vs. multidimensional
    or profile iti.e., only looking at the diagonal recurrent points, 
    as well as functions for optimization and plotting are proposed.
    in-depth measures of the whole cross-recurrence plot,
    Please refer to Coco and others (2021) <doi:10.32614/RJ-2021-062>,
    Coco and Dale (2014) <doi:10.3389/fpsyg.2014.00510> 
    and Wallot (2018) <doi: 10.1080/00273171.2018.1512846>
    for further details about the method.

A user friendly function 'crrcbcv' to compute bias-corrected variances for competing risks regression models using proportional subdistribution hazards with small-sample clustered data. Four types of bias correction are included: the MD-type bias correction by Mancl and DeRouen (2001) <doi:10.1111/j.0006-341X.2001.00126.x>, the KC-type bias correction by Kauermann and Carroll (2001) <doi:10.1198/016214501753382309>, the FG-type bias correction by Fay and Graubard (2001) <doi:10.1111/j.0006-341X.2001.01198.x>, and the MBN-type bias correction by Morel, Bokossa, and Neerchal (2003) <doi:10.1002/bimj.200390021>.

Extension of 'cmprsk' to Stratified and Clustered data.    
      A goodness of fit test for Fine-Gray model is also provided.        
      Methods are detailed in the following articles: Zhou et al. (2011) <doi:10.1111/j.1541-0420.2010.01493.x>,
      Zhou et al. (2012) <doi:10.1093/biostatistics/kxr032>, 
      Zhou et al. (2013) <doi: 10.1002/sim.5815>.

Performs forward and backward stepwise regression for the 
    proportional subdistribution hazards model in competing risks 
    (Fine & Gray 1999). Procedure uses AIC, BIC and BICcr as selection 
    criteria. BICcr has a penalty of k = log(n*), where n* is the number 
    of primary events. This version includes improved handling of factors, 
    interactions, and polynomial terms.