Integrated species distribution modeling is a rising field in quantitative ecology thanks to significant rises in the quantity of data available, increases in computational speed and the proven benefits of using such models. 
  Despite this, the general software to help ecologists construct such models in an easy-to-use framework is lacking. 
  We therefore introduce the R package 'PointedSDMs': which provides the tools to help ecologists set up integrated models and perform inference on them.
  There are also functions within the package to help run spatial cross-validation for model selection, as well as generic plotting and predicting functions.
  An introduction to these methods is discussed in Issac, Jarzyna, Keil, Dambly, Boersch-Supan, Browning, Freeman, Golding, Guillera-Arroita, Henrys, Jarvis, Lahoz-Monfort, Pagel, Pescott, Schmucki, Simmonds and O’Hara (2020) <doi:10.1016/j.tree.2019.08.006>.

Estimate specification models for the state-dependent level of an optimal quantile/expectile forecast.
  Wald Tests and the test of overidentifying restrictions are implemented. Plotting of the estimated specification model is possible.
  The package contains two data sets with forecasts and realizations: the daily accumulated precipitation at London, UK from the high-resolution model of the
  European Centre for Medium-Range Weather Forecasts (ECMWF, <https://www.ecmwf.int/>) and GDP growth Greenbook data by the US Federal Reserve.
  See Schmidt, Katzfuss and Gneiting (2015) <doi:10.48550/arXiv.1506.01917> for more details on the identification and estimation of a directive behind a point forecast.

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.