**Author details**

**Figure 12.** Initial joint distribution and set of ordinal joint distributions.

different ways.

110 Metrology

usual way.

factors.

**6.4. Indirect experiment**

easily solved by both MCM and MCD.

rank. Multiplying them we get the value of a rank measure. You can take advantage of this in a working experiment when the data about the same physical quantity comes in completely

For example, let's use the model whose distribution is shown in **Figure 12**. The received data is {(−0.5,0.5), (0.1, −0.4), (0.5,0.7)}. Their order is {(1, 2), (2, 1), (3, 3)}. The values of probabilities from the densities of ordinal distributions are {(0.578), (0.841), (1.114)}. Hence the value of a rank measure is 0.542. Next, it is possible to identify the shear and scattering parameters of the model in the

In the event that the statistical links between the factors are significant, the task is solved only numerically. For MCM, this is a direct numerical experiment. MCD is a search for direct and inverse transformations of such that make the distribution of the model independent by

In order to pass from the model of direct measurement to the model of the indirect measurement experiment, it is necessary to replace the measurand of trivial model by a more complex measurement principle model *x* = *f*(*ξ*, *υ*), where *ξ* and *ν* are the quantities measured from the direct measurement experiment. In a simple formulation, the problem of an indirect experiment consists in calculating the uncertainty function of the new measurand *u*(*x*), starting from the uncertainties obtained from the experimental data *u*(*ξ*) and *u*(*υ*). As a rule, the problem is

## Eugene Charnukha

Address all correspondence to: charnukha@tut.by

A. V. Luikov Heat and Mass Transfer Institute, National Academy of Sciences of Belarus, Minsk, Belarus
