arXiv subjects

Donald St. P. Richards

Publications and source records attributed to Donald St. P. Richards.

13 recordsLinked to original sources

arXiv2025

Hyperdeterminantal Total Positivity

For a given positive integer $m$, the concept of hyperdeterminantal total positivity is defined for a kernel $K\colon {\mathbb R}^{2m} \to {\mathbb R}$, thereby generalizing the classical concept of total positivity. Extending the fundamental example, $K(x,y) = \exp(xy)$, $x, y \in \mathbb{R}$, of a classical totally positive kernel, the hyperdeterminantal total positivity property of the kernel $K(x_1,\dots,x_{2m}) = \exp(x_1\cdots x_{2m})$, $x_1,\dots,x_{2m} \in \mathbb{R}$ is established. By applying Matsumoto's hyperdeterminantal Binet-Cauchy formula, we derive a generalization of Karlin's basic composition formula; then we use the generalized composition formula to construct several examples of hyperdeterminantal totally positive kernels. Further generalizations of hyperdeterminantal total positivity by means of the theory of finite reflection groups are described and some open problems are posed.

math.CA↗

arXiv2018

Return Optimization Securities and Other Remarkable Structured Investment Products: Indicators of Future Outcomes for U.S. Treasuries?

We analyze four structured products that have caused severe losses to investors in recent years. These products are: return optimization securities, yield magnet notes, reverse exchangeable securities, and principal-protected notes. We describe the basic structure of these products, analyze them probabilistically using the Law of Total Expectation, and assess the practical implications of buying them in the mid-2000s. By estimating expected rates of return under various scenarios, we conclude in each case that buyers were likely to experience grave difficulties from the start. By inspecting various prospectuses, we detect that many structured products were designed to the detriment of buyers and to the advantage of the issuing banks and broker-dealers. Therefore, we find it difficult to understand why any investment advisor, in exercising fiduciary care of clients' funds, would have advised a client to purchases these products in the mid-2000's. In light of these results, we fear that the on-going worldwide financial crisis will be lengthened because of these structured products and others even more arcane than the ones considered here. We note that problems caused by structured products have increased investors' fears about the economy and the financial markets, causing many of them to purchase U.S. Treasury securities at negative real-interest rates. This has caused increases in the prices of U.S. Treasuries to record levels, and we fear for the day when this trend reverses.

q-fin.ST↗

arXiv2018

A Probabilistic Analysis of Autocallable Optimization Securities

We consider in this paper some structured financial products, known as reverse convertible notes, that resulted in substantial losses to certain buyers of these notes in recent years. We shall focus on specific reverse convertible notes known as "Autocallable Optimization Securities with Contingent Protection Linked to the S\&P 500 Financial Index," because these notes are representative of the broad spectrum of reverse convertibles notes. Therefore, the analysis provided in this paper is applicable to many other reverse convertible notes. We begin by describing the notes in detail and identifying potential areas of confusion in the pricing supplement to the prospectus for the notes. We deduce two possible interpretations of the payment procedure for the notes and apply the Law of Total Expectation to develop a probabilistic analysis for each interpretation. We also determine the corresponding expected net payments to note-holders under various scenarios for the financial markets and show that, under a broad range of scenarios, note-holders were likely to suffer substantial losses. As a consequence, we infer that the prospectus is sufficiently complex that financial advisers generally lacked the mathematical knowledge and expertise to understand the prospectus completely. Therefore, financial advisers who recommended purchases of the notes did not have the knowledge and expertise that is required by a fiduciary relationship, hence were unable to exercise fiduciary duty, and ultimately misguided their clients. We conclude that these reverse convertibles notes were designed by financial institutions to insure themselves, against significant declines in the equities markets, at the expense of note-holders.

q-fin.ST↗

arXiv2017

Distance Correlation: A New Tool for Detecting Association and Measuring Correlation Between Data Sets

The difficulties of detecting association, measuring correlation, and establishing cause and effect have fascinated mankind since time immemorial. Democritus, the Greek philosopher, underscored well the importance and the difficulty of proving causality when he wrote, "I would rather discover one cause than gain the kingdom of Persia." To address the difficulties of relating cause and effect, statisticians have developed many inferential techniques. Perhaps the most well-known method stems from Karl Pearson's coefficient of correlation, which Pearson introduced in the late 19th century based on ideas of Francis Galton. I will describe in this lecture the recently-devised distance correlation coefficient and describe its advantages over the Pearson and other classical measures of correlation. We will examine an application of the distance correlation coefficient to data drawn from large astrophysical databases, where it is desired to classify galaxies according to various types. Further, the lecture will analyze data arising in the ongoing national discussion of the relationship between state-by-state homicide rates and the stringency of state laws governing firearm ownership. The lecture will also describe a remarkable singular integral which lies at the core of the theory of the distance correlation coefficient. We will see that this singular integral admits generalizations to the truncated Maclaurin expansions of the cosine function and to the theory of spherical functions on symmetric cones.

stat.OT↗

arXiv2016

Exact ZF Analysis and Computer-Algebra-Aided Evaluation in Rank-1 LoS Rician Fading

We study zero-forcing detection (ZF) for multiple-input/multiple-output (MIMO) spatial multiplexing under transmit-correlated Rician fading for an N_R X N_T channel matrix with rank-1 line-of-sight (LoS) component. By using matrix transformations and multivariate statistics, our exact analysis yields the signal-to-noise ratio moment generating function (m.g.f.) as an infinite series of gamma distribution m.g.f.'s and analogous series for ZF performance measures, e.g., outage probability and ergodic capacity. However, their numerical convergence is inherently problematic with increasing Rician K-factor, N_R , and N_T. We circumvent this limitation as follows. First, we derive differential equations satisfied by the performance measures with a novel automated approach employing a computer-algebra tool which implements Groebner basis computation and creative telescoping. These differential equations are then solved with the holonomic gradient method (HGM) from initial conditions computed with the infinite series. We demonstrate that HGM yields more reliable performance evaluation than by infinite series alone and more expeditious than by simulation, for realistic values of K , and even for N_R and N_T relevant to large MIMO systems. We envision extending the proposed approaches for exact analysis and reliable evaluation to more general Rician fading and other transceiver methods.

cs.IT↗

arXiv2014

Kurtosis Tests for Multivariate Normality with Monotone Incomplete Data

We consider the problem of testing multivariate normality when the data consists of a random sample of two-step monotone incomplete observations. We define for such data a generalization of Mardia's statistic for measuring kurtosis, derive the asymptotic non-null distribution of the statistic under certain regularity conditions and against a broad class of alternatives, and give an application to a well-known data set on cholesterol measurements.

math.ST↗

arXiv2014

Schur Complement Based Analysis of MIMO Zero-Forcing for Rician Fading

For multiple-input/multiple-output (MIMO) spatial multiplexing with zero-forcing detection (ZF), signal-to-noise ratio (SNR) analysis for Rician fading involves the cumbersome noncentral-Wishart distribution (NCWD) of the transmit sample-correlation (Gramian) matrix. An \textsl{approximation} with a \textsl{virtual} CWD previously yielded for the ZF SNR an approximate (virtual) Gamma distribution. However, analytical conditions qualifying the accuracy of the SNR-distribution approximation were unknown. Therefore, we have been attempting to exactly characterize ZF SNR for Rician fading. Our previous attempts succeeded only for the sole Rician-fading stream under Rician--Rayleigh fading, by writing it as scalar Schur complement (SC) in the Gramian. Herein, we pursue a more general, matrix-SC-based analysis to characterize SNRs when several streams may undergo Rician fading. On one hand, for full-Rician fading, the SC distribution is found to be exactly a CWD if and only if a channel-mean--correlation \textsl{condition} holds. Interestingly, this CWD then coincides with the \textsl{virtual} CWD ensuing from the \textsl{approximation}. Thus, under the \textsl{condition}, the actual and virtual SNR-distributions coincide. On the other hand, for Rician--Rayleigh fading, the matrix-SC distribution is characterized in terms of determinant of matrix with elementary-function entries, which also yields a new characterization of the ZF SNR. Average error probability results validate our analysis vs.~simulation.

cs.IT↗

arXiv2014

Interpreting the Distance Correlation Results for the COMBO-17 Survey

The accurate classification of galaxies in large-sample astrophysical databases of galaxy clusters depends sensitively on the ability to distinguish between morphological types, especially at higher redshifts. This capability can be enhanced through a new statistical measure of association and correlation, called the {\it distance correlation coefficient}, which has more statistical power to detect associations than does the classical Pearson measure of linear relationships between two variables. The distance correlation measure offers a more precise alternative to the classical measure since it is capable of detecting nonlinear relationships that may appear in astrophysical applications. We showed recently that the comparison between the distance and Pearson correlation coefficients can be used effectively to isolate potential outliers in various galaxy datasets, and this comparison has the ability to confirm the level of accuracy associated with the data. In this work, we elucidate the advantages of distance correlation when applied to large databases. We illustrate how the distance correlation measure can be used effectively as a tool to confirm nonlinear relationships between various variables in the COMBO-17 database, including the lengths of the major and minor axes, and the alternative redshift distribution. For these outlier pairs, the distance correlation coefficient is routinely higher than the Pearson coefficient since it is easier to detect nonlinear relationships with distance correlation. The V-shaped scatterplots of Pearson versus distance correlation coefficients also reveal the patterns with increasing redshift and the contributions of different galaxy types within each redshift range.

astro-ph.CO↗

arXiv2013

Long-term Variability in the Length of the Solar Cycle

The recent paucity of sunspots and the delay in the expected start of Solar Cycle 24 have drawn attention to the challenges involved in predicting solar activity. Traditional models of the solar cycle usually require information about the starting time and rise time as well as the shape and amplitude of the cycle. With this tutorial, we investigate the variations in the length of the sunspot number cycle and examine whether the variability can be explained in terms of a secular pattern. We identified long-term cycles in archival data from 1610 - 2000 using median trace analyses of the cycle length and power spectrum analyses of the (O-C) residuals of the dates of sunspot minima and maxima. Median trace analyses of data spanning 385 years indicate a cycle length with a period of 183 - 243 years, and a power spectrum analysis identifies a period of 188 $\pm$ 38 years. We also find a correspondence between the times of historic minima and the length of the sunspot cycle, such that the cycle length increases during the time when the number of spots is at a minimum. In particular, the cycle length was growing during the Maunder Minimum when almost no sunspots were visible on the Sun. Our study suggests that the length of the sunspot number cycle should increase gradually, on average, over the next $\sim$75 years, accompanied by a gradual decrease in the number of sunspots. This information should be considered in cycle prediction models to provide better estimates of the starting time of each cycle.

astro-ph.SR↗

arXiv2013

Distance Correlation Methods for Discovering Associations in Large Astrophysical Databases

High-dimensional, large-sample astrophysical databases of galaxy clusters, such as the Chandra Deep Field South COMBO-17 database, provide measurements on many variables for thousands of galaxies and a range of redshifts. Current understanding of galaxy formation and evolution rests sensitively on relationships between different astrophysical variables; hence an ability to detect and verify associations or correlations between variables is important in astrophysical research. In this paper, we apply a recently defined statistical measure called the distance correlation coefficient which can be used to identify new associations and correlations between astrophysical variables. The distance correlation coefficient applies to variables of any dimension; it can be used to determine smaller sets of variables that provide equivalent astrophysical information; it is zero only when variables are independent; and it is capable of detecting nonlinear associations that are undetectable by the classical Pearson correlation coefficient. Hence, the distance correlation coefficient provides more information than the Pearson coefficient. We analyze numerous pairs of variables in the COMBO-17 database with the distance correlation method and with the maximal information coefficient. We show that the Pearson coefficient can be estimated with higher accuracy from the corresponding distance correlation coefficient than from the maximal information coefficient. For given values of the Pearson coefficient, the distance correlation method has a greater ability than the maximal information coefficient to resolve astrophysical data into highly concentrated V-shapes, which enhances classification and pattern identification. These results are observed over a range of redshifts beyond the local universe and for galaxies from elliptical to spiral.

astro-ph.CO↗

arXiv2007

Counting and Locating the Solutions of Polynomial Systems of Maximum Likelihood Equations, II: The Behrens-Fisher Problem

Let $μ$ be a $p$-dimensional vector, and let $Σ_1$ and $Σ_2$ be $p \times p$ positive definite covariance matrices. On being given random samples of sizes $N_1$ and $N_2$ from independent multivariate normal populations $N_p(μ,Σ_1)$ and $N_p(μ,Σ_2)$, respectively, the Behrens-Fisher problem is to solve the likelihood equations for estimating the unknown parameters $μ$, $Σ_1$, and $Σ_2$. We shall prove that for $N_1, N_2 > p$ there are, almost surely, exactly $2p+1$ complex solutions of the likelihood equations. For the case in which $p = 2$, we utilize Monte Carlo simulation to estimate the relative frequency with which a typical Behrens-Fisher problem has multiple real solutions; we find that multiple real solutions occur infrequently.

math.ST↗

arXiv2006

Long-term Variability in the Length of the Solar Cycle

Detailed models of the solar cycle require information about the starting time and rise time as well as the shape and amplitude of the cycle. However, none of these models includes a discussion of the variations in the length of the cycle, which has been known to vary from $\sim$7 to 17 years. The focus of our study was to investigate whether this range was associated with a secular pattern in the length of the sunspot cycle. To provide a basis for the analysis of the long-term behavior of the Sun, we analyzed archival data of sunspot numbers from 1700 - 2005 and sunspot areas from 1874 - 2005. The independent techniques of power spectrum analysis and phase dispersion minimization were used to confirm the $\sim$11-year Schwabe Cycle, and to illustrate the large range in the length of this cycle. Long-term cycles were identified in archival data from 1610 -- 2000 using median trace analyses of the length of the cycle, and from power spectrum analyses of the (O-C) residuals of the dates of sunspot minima and maxima. The median trace analysis suggested that the cycle length had a period of 183 - 243 years, while the more precise power spectrum analysis identified a period of 188 $\pm$ 38 years. We found that the 188-year cycle was consistent with the variation of sunspot numbers and seems to be related to the Schwabe Cycle. We found a correlation between the times of historic minima and the length of the sunspot cycle such that the length of the cycle was usually highest when the actual number of sunspots was lowest. The cycle length was growing during the Maunder Minimum when there were almost no sunspots visible on the Sun. This information can now be used to improve the accuracy of the current solar cycle models, to better predict the starting time of a given cycle.

astro-ph↗

arXiv2004

Algebraic methods toward higher-order probability inequalities, II

Let (L,\preccurlyeq) be a finite distributive lattice, and suppose that the functions f_1,f_2:L\to R are monotone increasing with respect to the partial order \preccurlyeq. Given μa probability measure on L, denote by E(f_i) the average of f_i over L with respect to μ, i=1,2. Then the FKG inequality provides a condition on the measure μunder which the covariance, Cov(f_1,f_2):=E(f_1f_2)-E(f_1)E(f_2), is nonnegative. In this paper we derive a ``third-order'' generalization of the FKG inequality. We also establish fourth- and fifth-order generalizations of the FKG inequality and formulate a conjecture for a general mth-order generalization. For functions and measures on R^n we establish these inequalities by extending the method of diffusion processes. We provide several applications of the third-order inequality, generalizing earlier applications of the FKG inequality. Finally, we remark on some connections between the theory of total positivity and the existence of inequalities of FKG-type within the context of Riemannian manifolds.

math.PR↗