Search results for "multivariate statistic"
showing 10 items of 327 documents
Testing for Asymmetric Information in Insurance Markets: A Multivariate Ordered Regression Approach
2016
The positive correlation (PC) test is the standard procedure used in the empirical literature to detect the existence of asymmetric information in insurance markets. This article describes a new tool to implement an extension of the PC test based on a new family of regression models, the multivariate ordered logit, designed to study how the joint distribution of two or more ordered response variables depends on exogenous covariates. We present an application of our proposed extension of the PC test to the Medigap health insurance market in the United States. Results reveal that the risk–coverage association is not homogeneous across coverage and risk categories, and depends on individual so…
A Test of Covariance-Matrix Forecasting Methods
2015
Providing a more accurate covariance matrix forecast can substantially improve the performance of optimized portfolios. Using out-of-sample tests, in this article the author evaluates alternative covariance matrix-forecasting methods by looking at: (1) their forecast accuracy, (2) their ability to track the volatility of a minimum-variance portfolio, and (3) their ability to keep the volatility of a minimum-variance portfolio at a target level. The author finds large differences between the methods. The results suggest that shrinking the sample covariance matrix improves neither the forecast accuracy nor the performance of minimum-variance portfolios. In contrast, switching from the sample …
A Stochastic Variance Factor Model for Large Datasets and an Application to S&P Data
2008
The aim of this paper is to consider multivariate stochastic volatility models for large dimensional datasets. We suggest the use of the principal component methodology of Stock and Watson [Stock, J.H., Watson, M.W., 2002. Macroeconomic forecasting using diffusion indices. Journal of Business and Economic Statistics, 20, 147–162] for the stochastic volatility factor model discussed by Harvey, Ruiz, and Shephard [Harvey, A.C., Ruiz, E., Shephard, N., 1994. Multivariate Stochastic Variance Models. Review of Economic Studies, 61, 247–264]. We provide theoretical and Monte Carlo results on this method and apply it to S&P data.
Is the environmental performance of industrialized countries converging? A ‘SURE’ approach to testing for convergence
2008
In this paper, we test for convergence in the environmental performance of a sample of OECD countries, with data ranging from 1971 to 2002. First, we use Data Envelopment Analysis (DEA) to compute two environmental performance indicators (EPIs) in the production theory framework. Second, we propose the use of a sequential multivariate approach to test for convergence in environmental performance. These tests allow us to reconcile the time series literature with the cross-sectional dimension, which is basic when testing for convergence in regional blocs. The SURE technique is used, which allows for the existence of correlations across the series without imposing a common speed of mean revers…
Clustering and Polarization in the Distribution of Output: A Multivariate Perspective.
2013
Abstract Modeling the cross-country distribution of per capita income using mixture analysis provides a natural platform for the detection of clubs of countries. Unfortunately, these mixture methods, when based on a strictly univariate approach are limiting towards one’s ability to learn about the underlying process of the emergence of what constitutes a club. This paper takes a fresh look at the constitution of the emerging clubs in the distribution of cross-country output using bivariate and multivariate mixture analysis. Our results suggest that clubs are also forming in the main Solowian determinants of economic growth.
Hysteresis vs. natural rate of unemployment: new evidence for OECD countries
2004
Abstract The paper tests hysteresis effects in unemployment using panel data for 19 OECD countries. We apply a sequential procedure based in two multivariate augmented Dickey-Fuller test (ADF)-type panel unit root tests in a SURE framework. We strongly reject the joint null of hysteresis and find that only seven countries present evidence of hysteresis.
Biometric analysis of Brachionus plicatilis ecotypes from Spanish lagoons
1983
Univariate comparisons and several multivariate statistical analyses have been performed to study the morphometric variability of B. plicatilis. Both laboratory clones kept under constant conditions and natural populations from different Spanish lagoons and different times of the year have been compared. The results show that not only size, but also allometric coefficients are influenced by environmental factors. However, an important genetic component in the variation of shape and size has been visualized. A clear North-South ordination of the populations of the different lagoons and an important dispersion between their summer populations as well as great differences due to seasonal varia…
Prediction of type 2 diabetes mellitus based on nutrition data
2021
Abstract Numerous predictive models for the risk of type 2 diabetes mellitus (T2DM) exist, but a minority of them has implemented nutrition data so far, even though the significant effect of nutrition on the pathogenesis, prevention and management of T2DM has been established. Thus, in the present study, we aimed to build a predictive model for the risk of T2DM that incorporates nutrition data and calculates its predictive performance. We analysed cross-sectional data from 1591 individuals from the population-based Cooperative Health Research in the Region of Augsburg (KORA) FF4 study (2013–14) and used a bootstrap enhanced elastic net penalised multivariate regression method in order to bu…
Use of an artificial model of monitoring data to aid interpretation of principal component analysis
2000
Abstract An artificial data matrix of element concentrations at sampling locations was created which included six simulated gradients of correlated variables (Ca+Mg, Ni+V, Pb+Cu+Zn, Cd, Fe and K), representing a simplified model of a National survey. The data matrix model was used to explore the efficiency with which Principal Components Analysis (PCA), without and with Varimax rotation, could derive the imposed gradients. The dependence of PCA on outliers was decreased by log-transformation of data. The Components derived from non-rotated PCA were confounded by bipolar clusters and oblique gradients, both resulting in superimposition of two independent gradients on one Component. Therefore…
Unsupervised Anomaly and Change Detection With Multivariate Gaussianization
2022
Anomaly detection (AD) is a field of intense research in remote sensing (RS) image processing. Identifying low probability events in RS images is a challenging problem given the high dimensionality of the data, especially when no (or little) information about the anomaly is available a priori. While a plenty of methods are available, the vast majority of them do not scale well to large datasets and require the choice of some (very often critical) hyperparameters. Therefore, unsupervised and computationally efficient detection methods become strictly necessary, especially now with the data deluge problem. In this article, we propose an unsupervised method for detecting anomalies and changes …