Probabilistic Inferences for the Sample Pearson Product Moment Correlation

Pearson Product-Moment Correlation

A new method to evaluate the similarity of chromatographic fingerprints: weighted pearson product-moment correlation coefficient.

The Pearson product-moment correlation coefficient is being used to evaluate the similarity of the high-performance liquid chromatographic fingerprints of traditional Chinese medicine (TCM) in China. It is confirmed that a large range of peak areas produced the wrong results. A new algorithm concerning weighted Pearson product-moment correlation coefficient is proposed in this article. The resu...

Quotient Correlation : a Sample Based Alternative to Pearson ’ S Correlation

The quotient correlation is defined here as an alternative to Pearson’s correlation that is more intuitive and flexible in cases where the tail behavior of data is important. It measures nonlinear dependence where the regular correlation coefficient is generally not applicable. One of its most useful features is a test statistic that has high power when testing nonlinear dependence in cases whe...

A New Robust Blind Watermarking Scheme Based on Steerable pyramid and DCT using Pearson product moment correlation

In this paper, we present a new, robust digitalwatermarking scheme for ownership protection. Thescheme is based on Steerable Pyramid (SP) and discretecosine transform (DCT) using Pearson product momentcorrelation. During the process of watermark embedding,SP is performed on original host image, and correspondingoriented sub-band is selected to carry the watermark. DCT<lb...

The Rank Correlation Coefficient as an Indicator of the Product-Moment Correlation Coefficient for Small Samples

On the basis of 2200 small (10-100) samples obtained from four random number populations, it is shown that the rank correlation coefficient, p, is 88 adequate a measure of concordance 88 the Pearson product-moment correlation, T. The samples were obtained by using pseudo-random linear and normal number generators for bivariate populations with expected correlation cC'efficientB, r~, of 0.0 and ...