Influence of Monte Carlo generations applied for modelling of measuring instruments on maximum distance error

The paper presents a study of the influence of Monte Carlo (MC) generations, applied for modelling measuring instruments, on the maximum distance error. This modelling refers to the frequency domain and is based on the weighted least-squares (WLS) method. The MC generations were produced by the four pseudo-random number generators that are directly related to a Gaussian distribution. These generators are: Basic Box-Muller, Polar Box-Muller, Monty Python and Ratio of Uniforms. Thus, the main task of this paper is an assessment of the influence of the MC generations provided by these generators on the values of error. The effect of generator selection on the model parameters and associated uncertainties was also considered. The numerical calculations were carried out for the accelerometer PCB393B05 that was chosen as being examples of measuring instruments intended for the measurement of acceleration