Statistics

• Produce graphic or numeric frequency histograms of images or signature files.
• Extract summary statistics including minimum, maximum, total, sum, average, range, population and sample standard deviation for pixel groups.
• Evaluate relative richness, diversity (entropy), dominance index, fragmentation index, number of different classes, center versus neighbors and binary comparison matrix pattern measures.
• Calculate a relative frequency image of non-zero values over multiple images.
• Perform simple linear regression, multiple linear regression, and logistic regression analysis between two images or attribute values files.
• Calculate the best fit using up to a 9th order trend surface to a set of irregular cell control points by least-squares procedures.
• Compute Moran's I first lag autocorrelation statistic for an image, along with confidence test.
• Compute the density, variance and variance-mean ratio of quadrat cell counts.
• Compute mean center (weighted or not) of a point distribution and standard radius.
• Compute the compactness ratio of polygons given corresponding area and perimeter images.
• Determine all unique combinations of values in two qualitative images. Crosstabulate, crosscorrelate and calculate similarity statistics for image pairs.
• Compute statistics for measuring the similarity between two qualitative images, including specialized Kappa measures that discriminate between errors of quantity and errors of location.
• Measure the correspondence between a quantitative modeled image showing the likelihood that a particular class exists and a Boolean image of that class as it actually occurs.
• Create systematic, random and stratified random point sampling schemes.
• Create random images according to rectilinear, normal or log-normal models.
• Convert an image to standard scores.