A collection of functions useful in (vegetation) community analyses and ordinations. Includes automatic species selection for ordination diagrams, NMDS stress/scree plots, species response curves, merging of taxa as well as calculation and sorting of synoptic tables.

Divide and conquer approach for estimating low-rank and sparse coefficient matrix in the generalized co-sparse factor regression. Please refer the manuscript 'Mishra, Aditya, Dipak K. Dey, Yong Chen, and Kun Chen. Generalized co-sparse factor regression. Computational Statistics & Data Analysis 157 (2021): 107127' for more details.

A post-estimation method for categorical response models (CRM). 
    Inputs from objects of class serp(), clm(), polr(), multinom(), mlogit(), 
    vglm() and glm() are currently supported. Available tests include the 
    Hosmer-Lemeshow tests for the binary, multinomial and ordinal logistic 
    regression; the Lipsitz and the Pulkstenis-Robinson tests for the ordinal 
    models. The proportional odds, adjacent-category, and constrained continuation-ratio 
    models are particularly supported at ordinal level. Tests for the proportional 
    odds assumptions in ordinal models are also possible with the Brant and the 
    Likelihood-Ratio tests. Moreover, several summary measures of predictive strength 
    (Pseudo R-squared), and some useful error metrics, including, the brier 
    score, misclassification rate and logloss are also available for the 
    binary, multinomial and ordinal models. Ugba, E. R. and Gertheiss, J. (2018) 
    <http://www.statmod.org/workshops_archive_proceedings_2018.html>.

Graphical tools and goodness-of-fit tests for right-censored data:
             1. Kolmogorov-Smirnov, Cramér-von Mises, and Anderson-Darling tests,
                which use the empirical distribution function for complete data 
                and are extended for right-censored data.
             2. Generalized chi-squared-type test, which is based on the squared 
                differences between observed and expected counts using random 
                cells with right-censored data.
             3. A series of graphical tools such as probability or cumulative hazard 
                plots to guide the decision about the most suitable parametric model 
                for the data.
                These functions share several features as they can handle both 
                complete and right-censored data, and they provide parameter 
                estimates for the distributions under study.