Calculate Distance Measures for a Given List of Data Frames with Factors
Calculate the p_values matrix for each species, using Chebyshev distan...
Calculate the Euclidean distance of a factor in a dataframe.
Calculate the Mahalanobis distance for each species.
Calculate a Manhattan distance of a factor in a dataframe.
Generate a Microsoft Word document about the Chebyshev distance matrix...
Generate a Microsoft Word document about the Euclidean distance matrix...
Generate a Microsoft Word document about Mahalanobis distance matrix a...
Generate a Microsoft Word document about the Manhattan distance and th...
Calculate the p_values matrix for each species, using Chebyshev distan...
Calculate the p_values matrix for each species, using the Euclidean di...
Calculate p_values matrix for each species, using Mahalanobis distance...
Calculate the p_values matrix for each species, using Manhattan distan...
It provides functions that calculate Mahalanobis distance, Euclidean distance, Manhattan distance and Chebyshev distance between each pair of species in a list of data frames. These metrics are fundamental in various fields, such as cluster analysis, classification, and other applications of machine learning and data mining, where assessing similarity or dissimilarity between data is crucial. The package is designed to be flexible and easily integrated into data analysis workflows, providing reliable tools for evaluating distances in multidimensional contexts.