qat_analyse_histogram_test_2d: Perform a histogram test with a given metric
In qat: Quality Assurance Toolkit

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/qat_analyse_histogram_test_2d.R

This check divides the data into blocks, estimates their probability density functions by histograms and compares them by using a given metric.

1 2	qat_analyse_histogram_test_2d(measurement_vector, co_measurement_vector= measurement_vector, metric="EMD", blocksize=100, numofbars=65, factorofbar=100)

`measurement_vector`	The measurement vector (2d array), which should be tested.
`co_measurement_vector`	An optional second measurement vector (2d array), which is compared to the frst. The default is the first measurement vector.
`metric`	Metric of the comparison. Details see below.
`blocksize`	Number of elements in the first dimension, which should be used for each block.
`numofbars`	Number of bins of the histogram.
`factorofbar`	Correction factor for non-value bins.

The field will be divided into blocks in the first dimension, 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.

It returns a list with the following entries:

`field`	Result matrix of the comparison.
`blocksize`	Size of blocks in the first dimension.
`numofbars`	Number of bins of the used histograms.
`metric`	Used metric in the comparisons.
`runs`	Number of blocks, which are compared.

Andre Duesterhus

Duesterhus, A., Hense, A. (2012) Advanced Information Criterion for Environmental Data Quality Assurance, \_Advances in Science and Research\_, *8*, 99-104.

qat_analyse_histogram_test_1d

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)