Data analytics, statistics, and more
The post compares differences between simple random sampling and geographically stratified sampling. Stratified random sampling improves the spatial distribution of sample point locations by stratifying the field geographically and sampling randomly within each stratum. Different sampling patterns are compared using Monte Carlo simulations on a simulated population.
Environmental data are frequently left-censored, indicating that some values are less than the limit of quantification for the analytical methods employed. These data are problematic because censored (non-detect) values are known only to range between zero and the censoring limit. This complicates analysis of the data, including estimating statistical parameters, characterizing data distributions, and conducting inferential statistics. This post demonstrates various procedures and methods that are available in R for analyzing data containing a mixture of detects and non-detects. These methods make few or no assumptions about the data, or substitute arbitrary values (e.g., one-half the detection or reporting limit) for the non-detects.
Combining principal component analysis (PCA) and clustering methods are useful for reducing the dimension of a data set into a few continuous variables containing the most important information in the data. This post illustrates how to combine PCA and clustering methods to identify patterns in a data set using the R language for statistical computing and visualization.
This post presents and demonstrates several methods for exploratory spatial data analysis using the R language for statistical computing and visualization. These methods can be used for identifying spatial dependence patterns and spatial heterogeneity, which are critical components of variogram development and the kriging procedure.
This post presents and demonstrates several methods for natural neighbor interpolation using the R language for statistical computing and visualization. The results are compared to those obtain using ordinary kriging.