On some statistical properties of a stationary Gaussian process in the presence of measurement errors

Process outputs of many production processes like chemical, food processing and pharmaceutical industry follow a stationary Gaussian process. Some amount of measurement error always present in the measured data due to inaccurate measuring processes. Throughout this paper, we discuss some statistical properties like the mean and variance of a stationary Gaussian process when observed data are affected by measurement errors. As a special case, we discuss a stationary autoregressive process of order one with Gaussian white noise where measurement error follows an independent Gaussian distribution.