It uses 'phenological' and productivity-related variables derived from time series of vegetation 
    indexes, such as the Normalized Difference Vegetation Index, to assess ecosystem dynamics and change, which 
    eventually might drive to land degradation. The final result of the Land Productivity Dynamics indicator 
    is a categorical map with 5 classes of land productivity dynamics, ranging from declining to increasing 
    productivity. See www.sciencedirect.com/science/article/pii/S1470160X21010517/ for a description 
    of the methods used in the package to calculate the indicator.

A nonparametric method to approximate Laplacian graph spectra of a network with 
    ordered vertices. This provides a computationally efficient algorithm for obtaining an 
	accurate and smooth estimate of the graph Laplacian basis. The approximation results can 
	then be used for tasks like change point detection, k-sample testing, and so on. The 
	primary reference is Mukhopadhyay, S. and Wang, K. (2018, Technical Report).

Provides a bunch of algorithms based on linear programming for estimating, under 
    the homogeneity hypothesis, RxC ecological contingency tables (or vote transition matrices) 
    using mainly aggregate data (from voting units). 
    References: 
    Pavía and Romero (2022) <doi:10.1177/00491241221092725>.
    Pavía (2023) <doi:10.1007/s43545-023-00658-y>.
    Pavía and Romero (2024) <doi:10.1093/jrsssa/qnae013>.
    Pavía (2024) A local convergent ecological inference algorithm for RxC tables.
    Pavía and Penadés (2024). A bottom-up approach for ecological inference.
    Romero, Pavía, Martín and Romero (2020) <doi:10.1080/02664763.2020.1804842>.
    Acknowledgements:
    The authors wish to thank Consellería de Educación, Universidades y Empleo, Generalitat Valenciana (grant AICO/2021/257) and Ministerio de Economía e Innovación (grant PID2021-128228NB-I00) for supporting this research.

Functions to estimate the intensity function and its derivative of a given order of a multiplicative counting process using the local polynomial method.