R has no built-in pointer functionality. The 'pointr' package fills this gap and lets you create pointers to R objects, including subsets of dataframes. This makes your R code more readable and maintainable.

Functions to calculate and plot event and pointer years as well as resilience indices. Designed for dendroecological applications, but also suitable to analyze patterns in other ecological time series.

Generation of multiple count, binary and continuous variables simultaneously 
             given the marginal characteristics and association structure. Throughout the package,
             the word 'Poisson' is used to imply count data under the assumption of Poisson distribution. 
             The details of the method are explained in Amatya et al. (2015) <DOI:10.1080/00949655.2014.953534>.

Provides the probability, distribution, and quantile functions and random number generator for the Poisson-Binomial distribution.  This package relies on FFTW to implement the discrete Fourier transform, so that it is much faster than the existing implementation of the same algorithm in R.

Generation of multiple count, binary and ordinal variables simultaneously 
             given the marginal characteristics and association structure. Throughout the package,
             the word 'Poisson' is used to imply count data under the assumption of Poisson distribution. The details of the method are explained in Amatya, A. and Demirtas, H. (2015) <DOI:10.1080/00949655.2014.953534>.

Generation of a chosen number of count, binary, ordinal, and continuous random variables, with specified correlations and marginal properties. The details of the method are explained in Demirtas (2012) <DOI:10.1002/sim.5362>.

Generation of multiple count, binary, ordinal and normal variables simultaneously given the marginal characteristics and association structure.
             The details of the method are explained in Demirtas et al. (2012) <DOI:10.1002/sim.5362>.

Functions to create confidence intervals for ratios of Poisson
    rates under misclassification using double sampling. Implementations of the 
    methods described in Kahle, D., P. Young, B. Greer, and D. Young (2016). 
    "Confidence Intervals for the Ratio of Two Poisson Rates Under One-Way 
    Differential Misclassification Using Double Sampling." Computational 
    Statistics & Data Analysis, 95:122–132.