Serial Correlation Coefficient

Switching Activity in Bit-Serial Constant-Coefficient Serial/Parallel Multipliers

Bit-serial architectures have the advantage of high throughput, area efficient multipliers. These multipliers are implemented using shift-add operations [1], with full adders and D flip-flops as building blocks. Multiplication with a constant fixed-point coefficient is commonly used in digital signal processing (DSP) circuits, such as digital filters [2][3]. The design of a constant-coefficient...

Testing serial correlation in semiparametric varying coefficient partially linear errors-in-variables model

Abstract The authors propose a VN,p test statistic for testing finite-order serial correlation in a semiparametric varying coefficient partially linear errors-in-variables model. The test statistic is shown to have asymptotic normal distribution under the null hypothesis of no serial correlation. Some Monte Carlo experiments are conducted to examine the finite sample performance of the proposed...

Ensemble Correlation Coefficient

Elements in a sample date are demonstrated based on their characteristics and in turn the characteristics are represented by variables. Identifying the relationship between these variables is crucial for prediction, hypothesis testing, and decision making. The relation between two variables is often quantified using a correlation factor. Once correlation is known it can be used to make predicti...

Spearman Rank Correlation Coefficient

Spearman’s Rank Order Correlation Coefficient

• In this lesson, we will learn how to measure the coefficient of correlation for two sets of ranking. • The coefficient of correlation, r, measures the strength of association or correlation between two sets of data that can be measured. Sometimes, the data is not measurable but can only be ordered, as in ranking. • For example, two students can be asked to rank toast, cereals, and dim sum in ...

The Correlation Coefficient: An Overview

Correlation and regression are different, but not mutually exclusive, techniques. Roughly, regression is used for prediction (which does not extrapolate beyond the data used in the analysis) whereas correlation is used to determine the degree of association. There situations in which the x variable is not fixed or readily chosen by the experimenter, but instead is a random covariate to the y va...