RolWinMulCor: An R package for estimating rolling window multiple correlation in ecological time series

RolWinMulCor estimates the rolling window correlation for bi- and multi-variate cases between regular time series, with particular emphasis on ecological data. It is based on the concept of rolling, running or sliding window correlation, being useful for evaluating the evolution and stability of correlation over time. RolWinMulCor contains six functions to estimate and to plot the correlation coefficients and their respective p-values. The first two focus on the bi-variate case: (1) rolwincor_1win and (2) rolwincor_heatmap, estimate the correlation coefficients and the p-values for only one window-length (time-scale) and considering all possible window-lengths or a band of window-lengths, respectively. The second two functions: (3) rolwinmulcor_1win and (4) rolwinmulcor_heatmap, are designed to analyze the multi-variate case, following the bi-variate case to visually display the results, but these two approaches are methodologically different (the multi-variate case estimate the adjusted coefficients of determination instead of the correlation coefficients). The last two functions: (5) plot_1win and (6) plot_heatmap, are used to represent graphically the outputs of the four aforementioned functions as simple plots or as heat maps. The functions contained in RolWinMulCor are highly flexible, containing several parameters for controlling the estimation of correlation and the features of the plot output. The RolWinMulCor package also provides examples with synthetic and real-life ecological time series for illustrating its use.