This work discusses estimates based on rounded data. The work describes the estimates of parameters in time series AR and MA and in linear regression, the work presents different kinds of estimates based on rounded data. The work focuses on time series model AR(1) and linear regression, where simulations are added to theories and methods are compared on rounded and unrounded data. In addition, the comparison of linear regression is shown on the exemple of graph data. Powered by TCPDF (www.tcpdf.org)

Most recorded data are rounded to the nearest decimal place due to the precision of the recording mechanism. This rounding entails errors in estimation and measurement. In this paper, we compare the performances of three types of estimators based on rounded data from time series models, namely A-K corrected estimator, approximate MLE and the SOS estimator. In order to perform the comparison, the A-K corrected estimators for the MA(1) model are derived theoretically. To improve the efficiency of the estimation, two types of variance-reduction estimators are further proposed, which are based on linear combinations of aforementioned three estimators. Simulation results show the proposed variance reduction estimators significantly improve the estimation efficiency.

This work disusses estimates based on rounded data. The work describes the estimates of parameters in time series AR and MA and in linear regression, the work presents different kinds of estimates based on rounded data. The work focuses on time series model AR(1) and linear regression, where simulations are added to theories and methods are compared on rounded and unrounded data. In adition, the comparison of linear regression is shown at graphs. Powered by TCPDF (www.tcpdf.org)