Linearization region in the straight-line calibration

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F25%3A73634029" target="_blank" >RIV/61989592:15310/25:73634029 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1142/9789819800674_0030" target="_blank" >http://dx.doi.org/10.1142/9789819800674_0030</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1142/9789819800674_0030" target="_blank" >10.1142/9789819800674_0030</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Linearization region in the straight-line calibration

Popis výsledku v původním jazyce

We consider the statistical straight-line calibration model, which, as it turns out, is a nonlinear regression errors-in-variables model. Since the related measurement model to determine the straight-line parameters is generally nonlinear, the derived covariance matrix of the parameter estimators only provides approximations of the uncertainties. To address this, we introduce a statistical test that helps us determine whether the linearized statistical straight-line calibration model is suitable for the measured data. If the model demonstrates linearity, we can utilize the optimal estimators, the best linear unbiased estimators for the model parameters, along with their covariance matrix. Moreover, by including additional normality assumptions, we can calculate confidence intervals for any feasible linear combination of parameters. In particular, here we identify the linearization region of the straight-line calibration model and provide a simple sufficient condition for the model to be considered linearizable.

Název v anglickém jazyce

Linearization region in the straight-line calibration

Popis výsledku anglicky

We consider the statistical straight-line calibration model, which, as it turns out, is a nonlinear regression errors-in-variables model. Since the related measurement model to determine the straight-line parameters is generally nonlinear, the derived covariance matrix of the parameter estimators only provides approximations of the uncertainties. To address this, we introduce a statistical test that helps us determine whether the linearized statistical straight-line calibration model is suitable for the measured data. If the model demonstrates linearity, we can utilize the optimal estimators, the best linear unbiased estimators for the model parameters, along with their covariance matrix. Moreover, by including additional normality assumptions, we can calculate confidence intervals for any feasible linear combination of parameters. In particular, here we identify the linearization region of the straight-line calibration model and provide a simple sufficient condition for the model to be considered linearizable.

Druh

C - Kapitola v odborné knize

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název knihy nebo sborníku

Advanced Mathematical and Computational Tools in Metrology and Testing XIII

ISBN

978-981-9800-67-4

Počet stran výsledku

8

Strana od-do

330-337

Počet stran knihy

368

Název nakladatele

World Scientific Publishing Company

Místo vydání

Singapore

Kód UT WoS kapitoly

—