join_count: Test for Spatial Join Count Statistics

In r4pde: Companion to R for Plant Disease Epidemiology Book

Test for Spatial Join Count Statistics

Description

The function join_count calculates spatial join count statistics for a binary matrix, identifying patterns of aggregation or randomness.

Usage

join_count(matrix_data, verbose = TRUE)

Arguments

matrix_data	A binary matrix (with elements 0 and 1) representing the spatial distribution of two types of points: 0 for healthy plants (H) and 1 for diseased plants (D). This matrix reflects the geographical distribution or layout of plants in the studied area.
verbose	Logical. If TRUE (default), prints a formatted message to the console.

Details

The function conducts an analysis by first counting the occurrence of specific sequences ("01 or 10" and "11" - equivalent to HD and DD) in the binary matrix. It then calculates expected values, standard deviations, and Z-scores to determine the spatial randomness or aggregation. The analysis considers both horizontal and vertical adjacency (rook case) in the matrix.

Value

A comprehensive, rich-text formatted string of results that includes:

• Statistical counts of specific binary sequences (e.g., "01 or 10", "11")

• Expected counts under the assumption of Complete Spatial Randomness (CSR)

• Standard deviations and Z-scores (ZHD for "01 or 10" sequences, ZDD for "11" sequences)

• Interpretation of whether the spatial distribution for each sequence type is "Aggregated" or "Not Aggregated" based on Z-scores

• A summary explaining the implications of these statistics and patterns

The return value aims to provide a clear understanding of the spatial arrangement's characteristics, aiding in further spatial analysis or research.

References

Madden, L. V., Hughes, G., & van den Bosch, F. (2007). The Study of Plant Disease Epidemics. The American Phytopathological Society.

See Also

Other Spatial analysis: AFSD(), BPL(), count_subareas(), count_subareas_random(), fit_gradients(), oruns_test(), oruns_test_boustrophedon(), oruns_test_byrowcol(), plot_AFSD()

r4pde documentation built on July 2, 2025, 5:09 p.m.