Approximations of deviation fields of some nonparametic statistical estimates by gaussian fields, invariance principles

1983 ◽  
pp. 302-314 ◽  
Author(s):  
V. D. Konakov
Keyword(s):  
Gaussian Fields ◽  
Invariance Principles ◽  
Statistical Estimates

Selective statistical estimates of multi-year monthly concentrations of biogenous pollution of small rivers of the Northwest zone of the Russian Federation

2020 ◽  
pp. 9-13
Author(s):  
Sergey Kovalenko
Keyword(s):  
Statistical Processing ◽  
Point Of View ◽  
Small Rivers ◽  
Statistical Parameters ◽  
Monthly Data ◽  
Statistical Estimates ◽  
Scientific Task ◽  
The Russian Federation ◽  
Agricultural Areas

The management of surface watercourses is an urgent scientific task. The article presents the results of statistical processing of long-term monthly data of field observations of hydrological and hydrochemical parameters along the Upper Yerga small river in the Vologda region. Sampling estimates of statistical parameters are obtained, autocorrelation and correlation analyzes are performed. The limiting periods from the point of view of pollution for water receivers receiving wastewater from drained agricultural areas are identified.

APPLICATION OF HIGHER-ORDER STATISTICS TO ANALYZING NON-GAUSSIAN FIELDS OF SIGNALS

2016 ◽  
Vol 75 (15) ◽  
pp. 1321-1329
Author(s):  
V.A. Tikhonov ◽  
A.V. Tkalenko ◽  
V.E. Lapa
Keyword(s):  
Order Statistics ◽  
Higher Order ◽  
Higher Order Statistics ◽  
Gaussian Fields ◽  
Non Gaussian

scholarly journals Invariance Principles and Observability in Switched Systems with an Application in Consensus

2020 ◽  
pp. 1-1
Author(s):  
Ti-Chung Lee ◽  
Ying Tan ◽  
Youfeng Su ◽  
Iven Mareels
Keyword(s):  
Switched Systems ◽  
Invariance Principles

scholarly journals Sufficiency of a Gaussian power spectrum likelihood for accurate cosmology from upcoming weak lensing surveys

2021 ◽  
Author(s):  
Robin E Upham ◽  
Michael L Brown ◽  
Lee Whittaker
Keyword(s):  
Power Spectrum ◽  
Random Noise ◽  
Power Spectra ◽  
Stage Iv ◽  
Wishart Distribution ◽  
Weak Lensing ◽  
Dependence Structure ◽  
Gaussian Fields ◽  
Non Gaussian ◽  
Parameter Constraints

Abstract We investigate whether a Gaussian likelihood is sufficient to obtain accurate parameter constraints from a Euclid-like combined tomographic power spectrum analysis of weak lensing, galaxy clustering and their cross-correlation. Testing its performance on the full sky against the Wishart distribution, which is the exact likelihood under the assumption of Gaussian fields, we find that the Gaussian likelihood returns accurate parameter constraints. This accuracy is robust to the choices made in the likelihood analysis, including the choice of fiducial cosmology, the range of scales included, and the random noise level. We extend our results to the cut sky by evaluating the additional non-Gaussianity of the joint cut-sky likelihood in both its marginal distributions and dependence structure. We find that the cut-sky likelihood is more non-Gaussian than the full-sky likelihood, but at a level insufficient to introduce significant inaccuracy into parameter constraints obtained using the Gaussian likelihood. Our results should not be affected by the assumption of Gaussian fields, as this approximation only becomes inaccurate on small scales, which in turn corresponds to the limit in which any non-Gaussianity of the likelihood becomes negligible. We nevertheless compare against N-body weak lensing simulations and find no evidence of significant additional non-Gaussianity in the likelihood. Our results indicate that a Gaussian likelihood will be sufficient for robust parameter constraints with power spectra from Stage IV weak lensing surveys.

scholarly journals Statistical Estimates of the Pulsar Glitch Activity

Universe ◽  
2021 ◽  
Vol 7 (1) ◽  
pp. 8
Author(s):  
Alessandro Montoli ◽  
Marco Antonelli ◽  
Brynmor Haskell ◽  
Pierre Pizzochero
Keyword(s):  
Linear Regression ◽  
Upper Bound ◽  
Bootstrap Method ◽  
Waiting Times ◽  
Statistical Estimates ◽  
Equal Variance ◽  
Linear Fit ◽  
The Moment ◽  
The Bootstrap Method

A common way to calculate the glitch activity of a pulsar is an ordinary linear regression of the observed cumulative glitch history. This method however is likely to underestimate the errors on the activity, as it implicitly assumes a (long-term) linear dependence between glitch sizes and waiting times, as well as equal variance, i.e., homoscedasticity, in the fit residuals, both assumptions that are not well justified from pulsar data. In this paper, we review the extrapolation of the glitch activity parameter and explore two alternatives: the relaxation of the homoscedasticity hypothesis in the linear fit and the use of the bootstrap technique. We find a larger uncertainty in the activity with respect to that obtained by ordinary linear regression, especially for those objects in which it can be significantly affected by a single glitch. We discuss how this affects the theoretical upper bound on the moment of inertia associated with the region of a neutron star containing the superfluid reservoir of angular momentum released in a stationary sequence of glitches. We find that this upper bound is less tight if one considers the uncertainty on the activity estimated with the bootstrap method and allows for models in which the superfluid reservoir is entirely in the crust.

Association between early antibiotic exposure and risk of childhood weight gain and obesity: a systematic review and meta-analysis

2019 ◽  
Vol 32 (5) ◽  
pp. 439-445 ◽  
Author(s):  
Mohammad Aghaali ◽  
Seyed Saeed Hashemi-Nazari
Keyword(s):  
Systematic Review ◽  
Weight Gain ◽  
Childhood Obesity ◽  
Early Life ◽  
Meta Analysis ◽  
Healthy Children ◽  
Antibiotic Exposure ◽  
Statistical Estimates ◽  
Childhood Weight

Abstract Background Recent studies have shown that antibiotic exposure during infancy is associated with increased body mass in healthy children. This study was performed to investigate the association between early-life antibiotic exposure and risk of childhood obesity. Methods A systematic review and meta-analysis was performed to comprehensively and quantitatively determine the association between early antibiotic exposure and risk of childhood obesity. Various databases such as PubMed, Embase, Scopus, Web of Science, ProQuest, Cochrane and Google Scholar were searched. A random-effects meta-analysis was performed to pool the statistical estimates. Additionally, a subgroup analysis was performed based on the time of follow-up. Results Nineteen studies involving at least 671,681 participants were finally included. Antibiotic exposure in early life was significantly associated with risk of childhood weight gain and obesity (odds ratio [OR]: 1.05, 95% confidence interval [CI]: 1.04–1.06). Conclusions Antibiotic exposure in early life significantly increases the risk of childhood weight gain and obesity.

scholarly journals Invariance Principles for Parabolic Equations with Random Coefficients

1997 ◽  
Vol 149 (2) ◽  
pp. 377-414 ◽  
Author(s):  
Donald A. Dawson ◽  
Michael A. Kouritzin
Keyword(s):  
Parabolic Equations ◽  
Random Coefficients ◽  
Invariance Principles
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