Perform a histogram test with a given metric
This check divides the data into blocks, estimates their probability density functions by histograms and compares them by using a given metric.
qat_analyse_histogram_test_1d(measurement_vector, co_measurement_vector=measurement_vector, metric="EMD", blocksize=100, numofbars=65, factorofbar=100)
- The measurement vector, which should be tested.
- An optional second measurement vector, which is compared to the first. The default is the first measurement vector.
- Metric of the comparison. Details see below.
- Number of elements, which should be used for each block.
- Number of bins of the histogram.
- Correction factor for non-value bins.
The field will be divided into blocks, with a length given by the parameter blocksize. From these blocks histograms are computed and afterwards compared. As a metric for the comparison one of the following five options are usable: EMD: Earth Mover's Distance (default); KLD: Kullback-Leibler Distance; JSD: Jenson-Shannon Distance; RMS: Root Mean Square; MS: Mean Square. As a result a field is generated, which includes the results of the comparison between every combination of blocks.
Duesterhus, A., Hense, A. (2012) Advanced Information Criterion for Environmental Data Quality Assurance, \_Advances in Science and Research\_, *8*, 99-104.
vec <- array(rnorm(1000), c(100, 20)) vec[51:100, ] <- vec[51:100, ] + 2 result <- qat_analyse_histogram_test_2d(vec, metric="EMD", blocksize=4, numofbars=65) qat_plot_histogram_test(result$field, "test_emd_2d", result$blocksize, result$numofbars, "emd", result$runs)