Description Usage Arguments Details Value Author(s) References See Also Examples
View source: R/qat_analyse_histogram_test_kld_1d.R
This check divides the data into blocks, estimates their probability density functions by histograms and compares them by using the Kullback-Leibler Divergence.
1 2 | qat_analyse_histogram_test_kld_1d(measurement_vector, blocksize =
floor(length(measurement_vector)/20), numofbars = 65, factorofbar = 100)
|
measurement_vector |
The measurement vector, which should be tested |
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 vector 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 the Kullback-Leibler Divergence is used. 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. |
factorofbar |
Correction factor used for 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_kld_2d
, qat_analyse_histogram_test_jsd_1d
, qat_analyse_histogram_test_rms_1d
, qat_analyse_histogram_test_ms_1d
, qat_analyse_histogram_test_emd_1d
1 2 3 4 | vec <- c(rnorm(1000), round(rnorm(1000)))
result <- qat_analyse_histogram_test_kld_1d(vec, 50, 65, 100)
qat_plot_histogram_test(result$field, "test_kld_1d", result$blocksize,
result$numofbars, result$factorofbar, "kld", result$runs)
|
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