Data analytics, statistics, and more
Landscapes contain complex spatial patterns in the distribution of resources that vary over time. This post examines the spatial analysis of landscapes using base R functions complemented by contributed packages for spatial pattern analysis and for quantifying landscape characteristics.
This post presents single-well iterative thinning, which is a method to determine an optimal sampling frequency for groundwater monitoring wells and monitoring constituents.
Use a stochastic partial differential equation (SPDE) approach with Integrated Nested Laplace Approximation (INLA) to model the spatio-temporal behavior of PM10 concentrations measured in the North-Italian region of Piemonte.
The performance of Bayesian inference using a stochastic partial differential equation (SPDE) approach with Integrated Nested Laplace Approximation (INLA) for predicting zinc concentrations in soil at unsampled locations is compared with those obtained using kriging.
Multivariate statistical methods provide a means of exploring complex data sets for patterns and relationships from which hypotheses can be generated and subsequently tested. This post explores methods to manage non-detects when applying multivariate procedures to investigate (dis)similarities among data objects based on a set of descriptors.