Estimation in the Presence of Measurement errors

This study considers the problem of estimating the population distribution of independent random variables from error-contaminated samples. The measurement error is also assumed to be normally distributed. Since the observed distribution function is a convolution of the error distribution with the true underlying distribution, estimation of the latter is often referred to as a deconvolution problem. A thorough study of the relevant deconvolution literature in statistics is reported. The intention is to draw more specific connections between certain deconvolution methods and also to demonstrate the application of the statistical theory of estimation in the presence of measurement error.

Autorentext

Lwando Kondlo is statistician at Medical Research Council of South Africa. He holds a MSc (Stats) from the University of the Western Cape. His research interest include but not limited to the following: sample survey design and analysis, measurement error models, small area estimation- sample size allocation ndirect method of estimate