Baoxue Zhang
Northeastern Normal University, China
Title: Statistical analysis for rounding data.
Unless the model is discrete, data rounding is unavoidable in practical
measurement. However, the errors caused by rounding of data are almost
ignored by all classical statistical theories. Although some pioneers
have noticed this problem, few suitable approaches were proposed to deal
with this error. In this work, both by simulations as well as by
theoretical analysis, we demonstrate that the traditionally used sample
mean and sample variance, covariance are no longer consistent nor
asymptotically normal, when rounding errors are present. Also, by some
concrete examples when measurements are rounded to some extent, we
propose to use MLE or approximated MLE (AMLE) to estimate the parameters
and discuss the properties of them and tests based on the new estimators.
In particular, as an example, we shall discuss the limiting properties of
the new estimator of parameters in an AR(p) model and M A(q) model when
the observations are rounded.
Joint work with Zhidong Bai and Shurong Zheng.
