scholarly journals HOW TO AVOID THE ZERO-POWER TRAP IN TESTING FOR CORRELATION

2021 ◽  
pp. 1-33
Author(s):  
David Preinerstorfer
Keyword(s):  
Power Function ◽  
Regression Models ◽  
Strongly Correlated ◽  
Correlated Errors ◽  
Initial Test ◽  
Power Of Tests ◽  
Optimality Properties ◽  
Theoretical Results ◽  
Modified Test

In testing for correlation of the errors in regression models, the power of tests can be very low for strongly correlated errors. This counterintuitive phenomenon has become known as the “zero-power trap.” Despite a considerable amount of literature devoted to this problem, mainly focusing on its detection, a convincing solution has not yet been found. In this article, we first discuss theoretical results concerning the occurrence of the zero-power trap phenomenon. Then, we suggest and compare three ways to avoid it. Given an initial test that suffers from the zero-power trap, the method we recommend for practice leads to a modified test whose power converges to $1$ as the correlation gets very strong. Furthermore, the modified test has approximately the same power function as the initial test and thus approximately preserves all of its optimality properties. We also provide some numerical illustrations in the context of testing for network generated correlation.

scholarly journals An analysis of Italian university students’ performance through segmented regression models: gender differences in STEM courses

Genus ◽  
2021 ◽  
Vol 77 (1) ◽  
Author(s):  
Andrea Priulla ◽  
Nicoletta D’Angelo ◽  
Massimo Attanasio
Keyword(s):  
Gender Differences ◽  
Regression Models ◽  
First Year ◽  
Strongly Correlated ◽  
Segmented Regression ◽  
Freshmen Students ◽  
Female Performance ◽  
And Mathematics ◽  
The Relationship ◽  
Better Than

AbstractThis paper investigates gender differences in university performances in Science, Technology, Engineering and Mathematics (STEM) courses in Italy, proposing a novel application through the segmented regression models. The analysis concerns freshmen students enrolled at a 3-year STEM degree in Italian universities in the last decade, with a focus on the relationship between the number of university credits earned during the first year (a good predictor of the regularity of the career) and the probability of getting the bachelor degree within 4 years. Data is provided by the Italian Ministry of University and Research (MIUR). Our analysis confirms that first-year performance is strongly correlated to obtaining a degree within 4 years. Furthermore, our findings show that gender differences vary among STEM courses, in accordance with the care-oriented and technical-oriented dichotomy. Males outperform females in mathematics, physics, chemistry and computer science, while females are slightly better than males in biology. In engineering, female performance seems to follow the male stream. Finally, accounting for other important covariates regarding students, we point out the importance of high school background and students’ demographic characteristics.

SEMIPARAMETRIC EFFICIENCY BOUNDS FOR CONDITIONAL MOMENT RESTRICTION MODELS WITH DIFFERENT CONDITIONING VARIABLES

2015 ◽  
Vol 32 (4) ◽  
pp. 917-946 ◽  
Author(s):  
Marian Hristache ◽  
Valentin Patilea
Keyword(s):  
Regression Models ◽  
Supply And Demand ◽  
Simultaneous Equations ◽  
Conditional Moment ◽  
Efficient Score ◽  
Semiparametric Efficiency ◽  
Regression Quantile ◽  
New Applications ◽  
Theoretical Results ◽  
Moment Restriction

This paper addresses the problem of semiparametric efficiency bounds for conditional moment restriction models with different conditioning variables. We characterize such an efficiency bound, that in general is not explicit, as a limit of explicit efficiency bounds for a decreasing sequence of unconditional (marginal) moment restriction models. An iterative procedure for approximating the efficient score when this is not explicit is provided. Our theoretical results provide new insight for the theory of semiparametric efficiency bounds literature and open the door to new applications. In particular, we investigate a class of regression-like (mean regression, quantile regression,…) models with missing data, an example of a supply and demand simultaneous equations model and a generalized bivariate dichotomous model.

scholarly journals Dzyaloshinskii–Moriya Coupling in 3d Insulators

2019 ◽  
Vol 4 (4) ◽  
pp. 84 ◽  
Author(s):  
Alexander Moskvin
Keyword(s):  
Density Functional ◽  
Microscopic Theory ◽  
Strongly Correlated ◽  
Spin Orbital ◽  
Functional Theory ◽  
Different Types ◽  
Theoretical Results ◽  
Spin Orbital Coupling ◽  
Density Transfer ◽  
Super Exchange Interaction

We present an overview of the microscopic theory of the Dzyaloshinskii–Moriya (DM) coupling in strongly correlated 3d compounds. Most attention in the paper centers around the derivation of the Dzyaloshinskii vector, its value, orientation, and sense (sign) under different types of the (super)exchange interaction and crystal field. We consider both the Moriya mechanism of the antisymmetric interaction and novel contributions, in particular, that of spin–orbital coupling on the intermediate ligand ions. We have predicted a novel magnetic phenomenon, weak ferrimagnetism in mixed weak ferromagnets with competing signs of Dzyaloshinskii vectors. We revisit a problem of the DM coupling for a single bond in cuprates specifying the local spin–orbital contributions to the Dzyaloshinskii vector focusing on the oxygen term. We predict a novel puzzling effect of the on-site staggered spin polarization to be a result of the on-site spin–orbital coupling and the cation-ligand spin density transfer. The intermediate ligand nuclear magnetic resonance (NMR) measurements are shown to be an effective tool to inspect the effects of the DM coupling in an external magnetic field. We predict the effect of a strong oxygen-weak antiferromagnetism in edge-shared CuO 2 chains due to uncompensated oxygen Dzyaloshinskii vectors. We revisit the effects of symmetric spin anisotropy directly induced by the DM coupling. A critical analysis will be given of different approaches to exchange-relativistic coupling based on the cluster and the DFT (density functional theory) based calculations. Theoretical results are applied to different classes of 3d compounds from conventional weak ferromagnets ( α -Fe 2 O 3 , FeBO 3 , FeF 3 , RFeO 3 , RCrO 3 , ...) to unconventional systems such as weak ferrimagnets (e.g., RFe 1 - x Cr x O 3 ), helimagnets (e.g., CsCuCl 3 ), and parent cuprates (La 2 CuO 4 , ...).

scholarly journals Trend analysis of water quality series based on regression models with correlated errors

2011 ◽  
Vol 400 (3-4) ◽  
pp. 341-352 ◽  
Author(s):  
Jesús Abaurrea ◽  
Jesús Asín ◽  
Ana C. Cebrián ◽  
Miguel A. García-Vera
Keyword(s):  
Water Quality ◽  
Trend Analysis ◽  
Regression Models ◽  
Correlated Errors

Growth relationships of individual flowers during late stages of floral development of Rhododendron L. 'Prize' and 'Gloria'

1998 ◽  
Vol 76 (8) ◽  
pp. 1350-1358
Author(s):  
H Brent Pemberton ◽  
Harold F Wilkins ◽  
James S Hodges
Keyword(s):  
Regression Models ◽  
Polynomial Regression ◽  
Cold Treatment ◽  
Female Flower ◽  
Growth Patterns ◽  
Strongly Correlated ◽  
Floral Part ◽  
Growth Measurement ◽  
Hormonal Content ◽  
Polynomial Regression Models

Single terminal inflorescences from two-stemmed plants of Rhododendron L. cv. 'Prize' and 'Gloria' were recurrently sampled during a 9°C cold treatment and subsequent forcing period in an 18°C growth chamber until plants reached anthesis. At each sample period, bud length and width were measured on each inflorescence, while subtending bud scale, petal, stamen ('Gloria' only), style, peduncle and ovary length, ovary width, and flower weight were determined on the two most basally attached flowers within an inflorescence for each cultivar. Polynomial regression models were calculated for each floral growth measurement over time, except for bud length and width, for each of the four flowers within a cultivar. Comparison of regression models revealed differences in floral part growth patterns among the various flowers within each cultivar. During the first week of placement in 18°C forcing temperatures after the cold treatment, bud length was the only floral part to grow on 'Prize' plants, while only female flower parts grew on 'Gloria' plants. These results indicate differences in growth resumption patterns between cultivars after cold storage. However, petal and style length were strongly correlated to flower weight for both cultivars indicating that these measurements could be used in laboratory or field situations to determine the floral stage of growth. The growth equations described would be useful for controlling the variability among shoots and flowers for analytical determinations, such as hormonal content analysis, and for studying relationships of floral growth patterns to environmental stimuli that could be used to control flowering. The statistical techniques used in this research make it possible to reduce the number of plants for such studies, as measurements taken on different flowers on the same plant can be used for floral part growth comparisons despite the inherent correlation present between such measurements.Key words: morphology, dormancy, growth modeling, multivariate multiple regression, controlled environment.

Sign in / Sign up

Export Citation Format

Share Document