Introduction to Levit (1974) On the Optimality of Some Statistical Estimates

1997 ◽  
pp. 325-346
Author(s):  
J. F. Pfanzagl
Keyword(s):  
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.

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 Bevacizumab and Breast Cancer: A Meta-Analysis of First-Line Phase III Studies and a Critical Reappraisal of Available Evidence

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
José R. Rossari ◽  
Otto Metzger-Filho ◽  
Marianne Paesmans ◽  
Kamal S. Saini ◽  
Alessandra Gennari ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Fixed Effects ◽  
Meta Analysis ◽  
Metastatic Breast ◽  
Progression Free Survival ◽  
Phase Iii ◽  
First Line ◽  
Statistical Estimates ◽  
Treatment Indications ◽  
Phase Iii Studies

Background. Randomized studies have shown different magnitude of bevacizumab benefit in the treatment of advanced breast cancer. Regulatory agencies have modified bevacizumab treatment indications across different regions. In this study, we perform a meta-analysis of phase III studies aiming to interrogate the magnitude of bevacizumab benefit for the treatment of first-line HER2-negative metastatic breast cancer (MBC).Methods. Data from studies E2100, AVADO and RIBBON-1 were used to calculate the benefit of bevacizumab in terms of tumor overall response rate (ORR), progression-free survival (PFS), overall survival (OS), and toxicities. Combined statistical estimates of hazard ratios (HR) and odds ratios were calculated using fixed-effects or random-effects models.Results. A total of 2,695 patients were evaluated. Combining bevacizumab with different chemotherapy backbones resulted in a 30% risk reduction of PFS events (HR = 0.70; 95% confidence interval [CI], 0.57–0.86) and increased ORR (odds ratio 1.81; 95% CI, 1.53–2.14). No OS benefit could be demonstrated (HR = 0.95; 95% CI, 0.85–1.06). Bevacizumab significantly increased the incidence of adverse events such as proteinuria, hypertension and cardiovascular events.Conclusions. Bevacizumab combined with chemotherapy in the first-line treatment of MBC significantly improved ORR and PFS, but also increased grade 3-4 toxicities. No significant OS advantage was observed.

scholarly journals Asymptotic Distributions of M-Estimates for Parameters of Multivariate Time Series with Strong Mixing Property

2021 ◽  
Vol 5 (1) ◽  
pp. 19
Author(s):  
Alexander Kushnir ◽  
Alexander Varypaev
Keyword(s):  
Time Series ◽  
Asymptotic Normality ◽  
Multivariate Time Series ◽  
Asymptotic Properties ◽  
Asymptotic Distributions ◽  
Stationary Time Series ◽  
Strong Mixing ◽  
Statistical Estimates ◽  
Distribution Parameters ◽  
M Estimates

The publication is devoted to studying asymptotic properties of statistical estimates of the distribution parameters u∈Rq of a multidimensional random stationary time series zt∈Rm, t∈ℤ satisfying the strong mixing conditions. We consider estimates u^nδ(z¯n), z¯n=(z1T,…,znT)T∈Rmn that provide in asymptotic n→∞ the maximum values for some objective functions Qn(z¯n;u), which have properties similar to the well-known property of local asymptotic normality. These estimates are constructed by solving the equations δn(z¯n;u)=0, where δn(z¯n;u) are arbitrary functions for which δn(z¯n;u)−gradhQn(z¯n;u+n−1/2h)→0(n→∞) in Pn,u(z¯n)-probability uniformly on u∈U, were U is compact in Rq. In many cases, the estimates u^nδ(z¯n) have the same asymptotic properties as well-known M-estimates defined by equations u^nQ(z¯n)=arg maxu∈UQn(z¯n;u) but often can be much simpler computationally. We consider an algorithmic method for constructing estimates u^nδ(z¯n), which is similar to the accumulation method first proposed by R. Fischer and rigorously developed by L. Le Cam. The main theoretical result of the article is the proof of the theorem, in which conditions of the asymptotic normality of estimates u^nδ(z¯n) are formulated, and the expression is proposed for their matrix of asymptotic mean-square deviations limn→∞nEn,u{(u^δ(z¯n)−u)(u^δ(z¯n)−u)T}.

Estimation of the reliability of determination of filtering parameters of productive formations using multi-dimensional regression analysis

2021 ◽  
pp. 50-59
Author(s):  
D.A. Martyushev ◽  
◽  
I.N. Ponomareva ◽  
V.I. Galkin ◽  
Keyword(s):  
Regression Analysis ◽  
Multivariate Regression Analysis ◽  
Oil Fields ◽  
Technological Parameters ◽  
Recovery Method ◽  
Statistical Estimates ◽  
Production Analysis ◽  
Perm Krai ◽  
Pressure Stabilization

Determination of reliable values of filtration parameters of productive strata is the most important task of monitoring the processes of developing reserves. One of the most effective methods for solving the problem is hydrodynamic testing of wells using the pressure recovery method, as well as modern methods - the pressure stabilization method and the method based on production analysis (Decline Analyze). This article is devoted to the assessment of the reliability of these three methods in determining the filtration parameters of terrigenous and carbonate productive deposits of oil fields in the Perm Krai. To solve the problem, multivariate regression analysis was used. A series of multidimensional mathematical models of well flow rates was built using filtration parameters determined for each of the methods. It is proposed to consider the filtration parameters included in the models with the maximum statistical estimates of performance as the most reliable. With regard to the fields under consideration, it was found that in terrigenous reservoirs, all three methods demonstrate stable results. In carbonate reservoirs, reliable values of filtration parameters are determined by processing pressure build-up curves. Pressure stabilization and production analysis methods show less robust results and require additional research in order to develop sound recommendations for their practical application. Keywords: permeability; skin factor; pressure stabilization curve; decline analyze; liquid flow rate; geological and technological parameters; oil deposit; carbonate deposits.

India-2021: Middle class in pandemic conditions

2021 ◽  
pp. 14
Author(s):  
Elena A. Bragina
Keyword(s):  
Developing Countries ◽  
Middle Class ◽  
Gradual Increase ◽  
Population Group ◽  
Special Significance ◽  
Statistical Estimates ◽  
National Characteristics ◽  
The Difference ◽  
Definition Of ◽  
Sociological Studies

The article analyzes the conditions for the formation of the middle class in India. Shown is its important balancing role in the politics and economy of the country. The nature of the definition of "middle class", its special significance in developing countries is considered. Due to the difference in the applied criterion - the initial unit of account (employee, family, population group), due to the weakness of statistical services, the results of sociological studies, statistical estimates of the size of the middle class are often approximate. The work shows that the official and infor-mal (shadow) parts of the middle class coexist in the economies of developing countries in parallel.  The pressure of the COVID-19 pandemic on the development of the Indian middle class is taken into account.  The article examines the national characteristics of the formation of the middle class inherent in India. Due to the unclear definition of the criteria, the inconsistency of its assessments, the insufficient level of work of statistical organizations, information on the size of the middle class is inaccurate (according to various estimates, about 210-360 million people). Attention is paid to the formation of the rural middle class in India, rural residents make up a significant part of it (estimated at 48-66%).The forecast of the recovery of the Indian middle class ispresented. It is assumed that its quantitative growth, which was observed before the pandemic, and a gradual increase in influence will continue and will allow in the future. The topic is relevant, in demand by the Russian reader.

scholarly journals On the limit to resolution and information on basal properties obtainable from surface data on ice streams

2008 ◽  
Vol 2 (2) ◽  
pp. 167-178 ◽  
Author(s):  
G. H. Gudmundsson ◽  
M. Raymond
Keyword(s):  
Flow Line ◽  
Estimation Method ◽  
Optimal Estimation ◽  
Surface Flow ◽  
Ice Thickness ◽  
Ice Streams ◽  
Statistical Estimates ◽  
Surface Data ◽  
Highly Sensitive ◽  
Surface Measurements

Abstract. An optimal estimation method for simultaneously determining both basal slipperiness and basal topography from variations in surface flow velocity and topography along a flow line on ice streams and ice sheets is presented. We use Bayesian inference to update prior statistical estimates for basal topography and slipperiness using surface measurements along a flow line. Our main focus here is on how errors and spacing of surface data affect estimates of basal quantities and on possibly aliasing/mixing between basal slipperiness and basal topography. We find that the effects of spatial variations in basal topography and basal slipperiness on surface data can be accurately separated from each other, and mixing in retrieval does not pose a serious problem. For realistic surface data errors and density, small-amplitude perturbations in basal slipperiness can only be resolved for wavelengths larger than about 50 times the mean ice thickness. Bedrock topography is well resolved down to horizontal scale equal to about one ice thickness. Estimates of basal slipperiness are not significantly improved by accurate prior estimates of basal topography. However, retrieval of basal slipperiness is found to be highly sensitive to unmodelled errors in basal topography.

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