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Linear errors-in-variables models were studied first, probably because linear models were so widely used and they are easier than non-linear ones. Unlike standard least squares regression (OLS), extending errors in variables regression (EiV) from the simple to the multivariable case is not straightforward, unless one treats all variables in the same way i.e. assume equal reliability.
A practical application is an experiment in which one measures current, I, and voltage, V, on a resistor in order to determine the resistance, R, using Ohm's law, R = V / I. Given the measured variables with uncertainties, I ± σ I and V ± σ V, and neglecting their possible correlation, the uncertainty in the computed quantity, σ R, is:
Complexity for these models will then be chosen according to the needed performance and the type of application considered. Ability to define this model is part of sensors and IMU manufacturers know-how. Sensors and IMU models are computed in factories through a dedicated calibration sequence using multi-axis turntables and climatic chambers.
Different factors will affect the accuracy of the transfer alignment, such as reference information delay, mounting error, sensor measurement error, lever-arm effect [2] and flexure of the carrier body.
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The case shown, with deviations measured perpendicularly, arises when errors in x and y have equal variances. In statistics, Deming regression, named after W. Edwards Deming, is an errors-in-variables model that tries to find the line of best fit for a two-dimensional data set.
IQ imbalance is a performance-limiting issue in the design of a class of radio receivers known as direct conversion receivers. [a] These translate the received radio frequency (RF, or pass-band) signal directly from the carrier frequency to baseband using a single mixing stage.
Humidity also causes a variable delay, resulting in errors similar to ionospheric delay, but occurring in the troposphere. This effect is more localized than ionospheric effects, changes more quickly and is not frequency dependent. These traits make precise measurement and compensation of humidity errors more difficult than ionospheric effects. [2]