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Dorozhovets M. Computing Uncertainty of the Extreme Values in Random Samples [Електронний ресурс] / M. Dorozhovets, I. Bubela // Computing. - 2016. - Vol. 15, Issue 2. - С. 127-135. - Режим доступу: http://nbuv.gov.ua/UJRN/Computing_2016_15_2_8
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Dorozhovets M. Uncertainties of the estimators and parameters of distribution in measurements with multiply observations [Електронний ресурс] / M. Dorozhovets, A. Szlachta // Вимірювальна техніка та метрологія. - 2020. - Т. 81, Вип. 4. - С. 3-9. - Режим доступу: http://nbuv.gov.ua/UJRN/metrolog_2020_81_4_3 The article shows that the commonly used method of estimating the Type A uncertainty of measurements based on the standard deviation of estimators of population parameters does not meet the definition of uncertainty. For correct determination of the standard uncertainty, it is necessary to use the distribution of the corresponding population parameter at the values of population estimators determined from the experiment but not the probability distribution of the estimator. The joint probability distribution of population parameters can be derived by transforming the joint distribution of estimators using a Jacobian equal to the ratio of the scale parameter estimator to the population scale parameter itself. Independently on population distribution, the standard uncertainties of the location and scale parameters of the population depend on the number of observation n as a function of <$E 1 "/" sqrt {n~-~3}>, i.e. can be determined when n >>= 4. When the number of observations is small then the uncertainty value calculated by the usual method may differ significantly from the correct value. The given numerical example confirms this statement.
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Dorozhovets M. Direct solution of polynomial regression of order up to 3 [Електронний ресурс] / M. Dorozhovets // Вимірювальна техніка та метрологія. - 2022. - Т. 83, Вип. 3. - С. 35-44. - Режим доступу: http://nbuv.gov.ua/UJRN/metrolog_2022_83_3_8 This article presents results related to the direct solution of the polynomial regression parameters based on the analytical solving of regression equations. The analytical solution is based on the normalization of the values of independent quantity with equidistance steps. The proposed solution does not need to directly solve a system of polynomial regression equations. The direct expressions to calculate estimators of regression coefficients, their standard deviations, and also standard and expanded deviation of polynomial functions are given. For a given number of measurement points, the parameters of these expressions have the same values independently of the range of input quantity. The proposed solution is illustrated by a numerical example used from a literature source.
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Dorozhovets M. Type B uncertainty of two-channel measurements [Електронний ресурс] / M. Dorozhovets // Український метрологічний журнал. - 2022. - № 4. - С. 24-29. - Режим доступу: http://nbuv.gov.ua/UJRN/Umlzh_2022_4_6
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