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Related papers: Yule's "nonsense correlation" solved: Part II

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In this paper, we resolve a longstanding open statistical problem. The problem is to mathematically confirm Yule's 1926 empirical finding of "nonsense correlation" (\cite{Yule}). We do so by analytically determining the second moment of the…

Statistics Theory · Mathematics 2016-08-31 Philip Ernst , Larry Shepp , Abraham Wyner

The purpose of this paper is to provide an exact formula for the second moment of the empirical correlation of two independent Gaussian random walks as well as implicit formulas for higher moments. The proofs are based on a symbolically…

Probability · Mathematics 2021-09-28 Philip A. Ernst , Dongzhou Huang , Frederi G. Viens

Yule (1926) identified the issue of "nonsense correlations" in time series data, where dependence within each of two random vectors causes overdispersion -- i.e. variance inflation -- for measures of dependence between the two. During the…

Statistics Theory · Mathematics 2024-02-06 Sohom Bhattacharya , Rajarshi Mukherjee , Elizabeth Ogburn

In this paper, we study the distribution of the so-called "Yule's nonsense correlation statistic" on a time interval $[0,T]$ for a time horizon $T>0$ , when $T$ is large, for a pair $(X_{1},X_{2})$ of independent Ornstein-Uhlenbeck…

Probability · Mathematics 2021-08-09 Soukaina Douissi , Frederi G. Viens , Khalifa Es-Sebaiy

We study the continuous-time version of the empirical correlation coefficient between the paths of two possibly correlated Ornstein-Uhlenbeck processes, known as Yule's nonsense correlation for these paths. Using sharp tools from the…

Probability · Mathematics 2025-04-25 Soukaina Douissi , Philip Ernst , Frederi Viens

Since the two seminal papers by Fisher (1915, 1921) were published, the test under a fixed value correlation coefficient null hypothesis for the bivariate normal distribution constitutes an important statistical problem. In the framework of…

Statistics Theory · Mathematics 2022-09-27 María Jaenada , Elena Castilla , Nirian Martín , Leandro Pardo

In this paper, a robust non-parametric measure of statistical dependence, or correlation, between two random variables is presented. The proposed coefficient is a permutation-like statistic that quantifies how much the observed sample S_n :…

Methodology · Statistics 2020-07-27 Rami Mahdi

Assume that $X$ and $Y$ are independent random variables, each having a Cauchy distribution with a known median. Taking a random independent sample of size $n$ of each $X$ and $Y$, one can then compute their centralized empirical…

Statistics Theory · Mathematics 2018-12-31 Veson Lee , Jan Vrbik

The paper written in 1925 by G. Udny Yule that we celebrate in this special issue introduces several novelties and results that we recall in detail. First, we discuss Yule (1925)'s main legacies over the past century, focusing on empirical…

Populations and Evolution · Quantitative Biology 2024-09-24 Amaury Lambert

Let a sequence of iid. random variables $\xi_1,...,\xi_n$ be given on a measurable space $(X,\cal X)$ with distribution $\mu$ together with a function $f(x_1,...,x_k)$ on the product space $(X^k,{\cal X}^k)$. Let $\mu_n$ denote the…

Probability · Mathematics 2007-05-23 Peter Major

Barlow (1985) hypothesized that the co-occurrence of two events $A$ and $B$ is "suspicious" if $P(A,B) \gg P(A) P(B)$. We first review classical measures of association for $2 \times 2$ contingency tables, including Yule's $Y$ (Yule, 1912),…

Machine Learning · Computer Science 2023-03-03 Christopher K. I. Williams

Let $\prec$ be the product order on $\mathbb{R}^k$ and assume that $X_1,X_2,\ldots,X_n$ ($n\geq3$) are i.i.d. random vectors distributed uniformly in the unit hypercube $[0,1]^k$. Let $S$ be the (random) set of vectors in $\mathbb{R}^k$…

Probability · Mathematics 2022-09-02 Royi Jacobovic , Or Zuk

Let $S_n^{(2)}$ denote the iterated partial sums. That is, $S_n^{(2)}=S_1+S_2+ ... +S_n$, where $S_i=X_1+X_2+ ... s+X_i$. Assuming $X_1, X_2,....,X_n$ are integrable, zero-mean, i.i.d. random variables, we show that the persistence…

Probability · Mathematics 2015-06-05 Amir Dembo , Jian Ding , Fuchang Gao

Let X_n=(x_{ij}) be an n by p data matrix, where the n rows form a random sample of size n from a certain p-dimensional population distribution. Let R_n=(\rho_{ij}) be the p\times p sample correlation matrix of X_n; that is, the entry…

Probability · Mathematics 2009-09-29 Tiefeng Jiang

Let $X_1, \ldots , X_n$ be mutually independent exponential random variables with distinct hazard rates $\lambda_1, \ldots , \lambda_n > 0$ and let $Y_1, \ldots, Y_n$ be a random sample from the exponential distribution with hazard rate…

Probability · Mathematics 2022-02-17 Subhash Kochar

(To appear in The American Statistician.) Distance covariance (Sz\'ekely, Rizzo, and Bakirov, 2007) is a fascinating recent notion, which is popular as a test for dependence of any type between random variables $X$ and $Y$. This approach…

Methodology · Statistics 2024-07-08 Jakob Raymaekers , Peter J. Rousseeuw

We consider so-called univariate unlinked (sometimes ``decoupled,'' or ``shuffled'') regression when the unknown regression curve is monotone. In standard monotone regression, one observes a pair $(X,Y)$ where a response $Y$ is linked to a…

Methodology · Statistics 2021-07-30 Fadoua Balabdaoui , Charles R. Doss , Cécile Durot

In some applications, an experimental unit is composed of two distinct but related subunits. The response from such a unit is $(X_{1}, X_{2})$ but we observe only $Y_1 = \min\{X_{1},X_{2}\}$ and $Y_2 = \max\{X_{1},X_{2}\}$, i.e., the…

Statistics Theory · Mathematics 2019-05-07 Jiahua Chen , Pengfei Li , Jing Qin , Tao Yu

In this paper, we are interested in the asymptotic behaviour of the sequence of processes $(W_n(s,t))_{s,t\in[0,1]}$ with \begin{equation*} W_n(s,t):=\sum_{k=1}^{\lfloor nt\rfloor}\big(1_{\{\xi_{S_k}\leq s\}}-s\big) \end{equation*} where…

Probability · Mathematics 2019-12-17 Nadine Guillotin-Plantard , Francoise Pene , Martin Wendler

The Yule-Simpson paradox notes that an association between random variables can be reversed when averaged over a background variable. Cox and Wermuth (2003) introduced the concept of distribution dependence between two random variables X…

Methodology · Statistics 2011-10-11 P. Vellaisamy
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