Correcting the Errors : A Note on Volatility Forecast Evaluation Based on High-Frequency Data and Realized Volatilities

This note develops general model-free adjustment procedures for the calculation of unbiased volatility loss functions based on practically feasible realized volatility benchmarks. The procedures, which exploit the recent asymptotic distributional results in Barndorff-Nielsen and Shephard (2002a), are both easy to implement and highly accurate in empirically realistic situations. On properly accounting for the measurement errors in the volatility forecast evaluations reported in Andersen, Bollerslev, Diebold and Labys (2003), the adjustments result in markedly higher estimates for the true degree of return-volatility predictability.

Isolated greater tuberosity fractures of the proximal humerus : validation and clinical implications for a new radiologic measurement method and classification

Pre-publication drafts are reproduced with permission and copyright © 2013 of the Journal of Orthopaedic Trauma [Mutch J, Rouleau DM, Laflamme GY, Hagemeister N. Accurate Measurement of Greater Tuberosity Displacement without Computed Tomography: Validation of a method on Plain Radiography to guide Surgical Treatment. J Orthop Trauma. 2013 Nov 21: Epub ahead of print.] and copyright © 2014 of the British Editorial Society of Bone and Joint Surgery [Mutch JAJ, Laflamme GY, Hagemeister N, Cikes A, Rouleau DM. A new morphologic classification for greater tuberosity fractures of the proximal humerus: validation and clinical Implications. Bone Joint J 2014;96-B:In press.]

The effects of environmental perturbation and measurement error on estimates of the shape parameter in the theta-logistic model of population regulation

The theta-logistic is a widely used generalisation of the logistic model of regulated biological processes which is used in particular to model population regulation. Then the parameter theta gives the shape of the relationship between per-capita population growth rate and population size. Estimation of theta from population counts is however subject to bias, particularly when there are measurement errors. Here we identify factors disposing towards accurate estimation of theta by simulation of populations regulated according to the theta-logistic model. Factors investigated were measurement error, environmental perturbation and length of time series. Large measurement errors bias estimates of theta towards zero. Where estimated theta is close to zero, the estimated annual return rate may help resolve whether this is due to bias. Environmental perturbations help yield unbiased estimates of theta. Where environmental perturbations are large, estimates of theta are likely to be reliable even when measurement errors are also large. By contrast where the environment is relatively constant, unbiased estimates of theta can only be obtained if populations are counted precisely Our results have practical conclusions for the design of long-term population surveys. Estimation of the precision of population counts would be valuable, and could be achieved in practice by repeating counts in at least some years. Increasing the length of time series beyond ten or 20 years yields only small benefits. if populations are measured with appropriate accuracy, given the level of environmental perturbation, unbiased estimates can be obtained from relatively short censuses. These conclusions are optimistic for estimation of theta. (C) 2008 Elsevier B.V All rights reserved.

Hypotheses Testing on a Multivariate Null Intercept Errors-in-Variables Model

Considering the Wald, score, and likelihood ratio asymptotic test statistics, we analyze a multivariate null intercept errors-in-variables regression model, where the explanatory and the response variables are subject to measurement errors, and a possible structure of dependency between the measurements taken within the same individual are incorporated, representing a longitudinal structure. This model was proposed by Aoki et al. (2003b) and analyzed under the bayesian approach. In this article, considering the classical approach, we analyze asymptotic test statistics and present a simulation study to compare the behavior of the three test statistics for different sample sizes, parameter values and nominal levels of the test. Also, closed form expressions for the score function and the Fisher information matrix are presented. We consider two real numerical illustrations, the odontological data set from Hadgu and Koch (1999), and a quality control data set.

Improved maximum likelihood estimators in a heteroskedastic errors-in-variables model

This paper develops a bias correction scheme for a multivariate heteroskedastic errors-in-variables model. The applicability of this model is justified in areas such as astrophysics, epidemiology and analytical chemistry, where the variables are subject to measurement errors and the variances vary with the observations. We conduct Monte Carlo simulations to investigate the performance of the corrected estimators. The numerical results show that the bias correction scheme yields nearly unbiased estimates. We also give an application to a real data set.

Bayesian estimation of regression parameters in elliptical measurement error models

The main object of this paper is to discuss the Bayes estimation of the regression coefficients in the elliptically distributed simple regression model with measurement errors. The posterior distribution for the line parameters is obtained in a closed form, considering the following: the ratio of the error variances is known, informative prior distribution for the error variance, and non-informative prior distributions for the regression coefficients and for the incidental parameters. We proved that the posterior distribution of the regression coefficients has at most two real modes. Situations with a single mode are more likely than those with two modes, especially in large samples. The precision of the modal estimators is studied by deriving the Hessian matrix, which although complicated can be computed numerically. The posterior mean is estimated by using the Gibbs sampling algorithm and approximations by normal distributions. The results are applied to a real data set and connections with results in the literature are reported. (C) 2011 Elsevier B.V. All rights reserved.

Passive angle measurement based localization consistency via geometric constraints

In this paper, we examine the geometric relations between various measured parameters and their corresponding errors in angle-measurement based emitter localization scenarios. We derive a geometric constraint formulating the relationship among the measurement errors in such a scenario. Using this constraint, we formulate the localization task as a constrained optimization problem that can be performed on the measurements in order to provide the optimal values such that the solution is consistent with the underlying geometry.

Comparative analysis for reactive energy measurement methodologies, under non-sinusoidal conditions in three-phase four-wire circuits

This paper presents some methodologies for reactive energy measurement, considering three modern power theories that are suitable for three-phase four-wire non-sinusoidal and unbalanced circuits. The theories were applied in some profiles collected in electrical distribution systems which have real characteristics for voltages and currents measured by commercial reactive energy meters. The experimental results are presented in order to analyze the accuracy of the methodologies, considering the standard IEEE 1459-2010 as a reference. Finally, for additional comparisons, the theories will be confronted with the modern Yokogawa WT3000 energy meter and three samples of a commercial energy meter through an experimental setup. © 2011 IEEE.

Influence Assessment in an Heteroscedastic Errors-in-Variables Model

The main goal of this article is to consider influence assessment in models with error-prone observations and variances of the measurement errors changing across observations. The techniques enable to identify potential influential elements and also to quantify the effects of perturbations in these elements on some results of interest. The approach is illustrated with data from the WHO MONICA Project on cardiovascular disease.

Non-invasive phakometric measurement of corneal and crystalline lens alignment in human eyes

We describe a non-invasive phakometric method for determining corneal axis rotation relative to the visual axis (β) together with crystalline lens axis tilt (α) and decentration (d) relative to the corneal axis. This does not require corneal contact A-scan ultrasonography for the measurement of intraocular surface separations. Theoretical inherent errors of the method, evaluated by ray tracing through schematic eyes incorporating the full range of human ocular component variations, were found to be larger than the measurement errors (β < 0.67°, α < 0.72° and d < 0.08 mm) observed in nine human eyes with known ocular component dimensions. Intersubject variations (mean ± S.D.: β = 6.2 ± 3.4° temporal, α = 0.2 ± 1.8° temporal and d = 0.1 ± 0.1 mm temporal) and repeatability (1.96 × S.D. of difference between repeat readings: β ± 2.0°, α ± 1.8° and d ± 0.2 mm) were studied by measuring the left eyes of 45 subjects (aged 18-42 years, 29 females and 16 males, 15 Caucasians, 29 Indian Asians, one African, refractive error range -7.25 to +1.25 D mean spherical equivalent) on two occasions. © 2005 The College of Optometrists.

Effectively simultaneous temperature and strain measurement utilising a dual-grating sensor formed by type IA and type IIA FBGs

In this paper, we report a systematic investigation of the dependence of both temperature and strain sensitivities on the jiber Bragg grating (FBG) type, including the wellknown Type I, Type IIA, and a new type which we have designated Type 1.4, using both hydrogen-Ji-ee and hydrogenated B/Ge codoped jibers. We have identijed distinct sensitivity characteristics for each grating type, and we have utilised them to implement a novel dual-grating, duul-parameter sensor device. Three dual-grating sensing schemes with different combinations of gruting types have been constructed and compared. The Type IA-Type IIA combination exhibits the best pe$ormance and is superior to that of previously reported gruting-based structures. The characteristics of the measurement errors in such dualgrating sensor systems is also presented in detail.

Effectively simultaneous temperature and strain measurement utilising a dual-grating sensor formed by type IA and type IIA FBGs

In this paper, we report a systematic investigation of the dependence of both temperature and strain sensitivities on the jiber Bragg grating (FBG) type, including the wellknown Type I, Type IIA, and a new type which we have designated Type 1.4, using both hydrogen-Ji-ee and hydrogenated B/Ge codoped jibers. We have identijed distinct sensitivity characteristics for each grating type, and we have utilised them to implement a novel dual-grating, duul-parameter sensor device. Three dual-grating sensing schemes with different combinations of gruting types have been constructed and compared. The Type IA-Type IIA combination exhibits the best pe$ormance and is superior to that of previously reported gruting-based structures. The characteristics of the measurement errors in such dualgrating sensor systems is also presented in detail.

Hydrological consequences of land-cover change: Quantifying the influence of plants on soil moisture with time-lapse electrical resistivity

Electrical resistivity of soils and sediments is strongly influenced by the presence of interstitial water. Taking advantage of this dependency, electrical-resistivity imaging (ERI) can be effectively utilized to estimate subsurface soil-moisture distributions. The ability to obtain spatially extensive data combined with time-lapse measurements provides further opportunities to understand links between land use and climate processes. In natural settings, spatial and temporal changes in temperature and porewater salinity influence the relationship between soil moisture and electrical resistivity. Apart from environmental factors, technical, theoretical, and methodological ambiguities may also interfere with accurate estimation of soil moisture from ERI data. We have examined several of these complicating factors using data from a two-year study at a forest-grassland ecotone, a boundary between neighboring but different plant communities.At this site, temperature variability accounts for approximately 20-45 of resistivity changes from cold winter to warm summer months. Temporal changes in groundwater conductivity (mean=650 S/cm =57.7) and a roughly 100-S/cm spatial difference between the forest and grassland had only a minor influence on the moisture estimates. Significant seasonal fluctuations in temperature and precipitation had negligible influence on the basic measurement errors in data sets. Extracting accurate temporal changes from ERI can be hindered by nonuniqueness of the inversion process and uncertainties related to time-lapse inversion schemes. The accuracy of soil moisture obtained from ERI depends on all of these factors, in addition to empirical parameters that define the petrophysical soil-moisture/resistivity relationship. Many of the complicating factors and modifying variables to accurately quantify soil moisture changes with ERI can be accounted for using field and theoretical principles.

An efficient DSE using conditional multivariate complex Gaussian distribution

This paper presents an efficient noniterative method for distribution state estimation using conditional multivariate complex Gaussian distribution (CMCGD). In the proposed method, the mean and standard deviation (SD) of the state variables is obtained in one step considering load uncertainties, measurement errors, and load correlations. In this method, first the bus voltages, branch currents, and injection currents are represented by MCGD using direct load flow and a linear transformation. Then, the mean and SD of bus voltages, or other states, are calculated using CMCGD and estimation of variance method. The mean and SD of pseudo measurements, as well as spatial correlations between pseudo measurements, are modeled based on the historical data for different levels of load duration curve. The proposed method can handle load uncertainties without using time-consuming approaches such as Monte Carlo. Simulation results of two case studies, six-bus, and a realistic 747-bus distribution network show the effectiveness of the proposed method in terms of speed, accuracy, and quality against the conventional approach.

Changes in depression during and following pregnancy

Rates of depression were studied in a sample of over 9000 women who were participants in the Avon Longitudinal Study of Pregnancy and Childhood. Assessments of depression were made at 18 and 32 weeks gestation, and at 8 and 32 weeks postpartum. Changes in depressive status across time were modelled using latent Markov modelling methods. This analysis showed that when classification errors were taken into account there was relatively high stability in diagnostic status during pregnancy and after pregnancy. However, the transition from late pregnancy to the early postnatal period showed evidence of increased instability and remission of depression. The net effects of this were that rates of depression tended to decline following childbirth. The implications of these results for a series of issues including measurement errors in depression reports and the prevalence of depression before and after childbirth are discussed.