On estimating the non-centrality parameter of a chi-squared distribution

Non-central chi-squared distribution plays a vital role in commonly used statistical testing procedures. The non-centrality parameter [delta] provides valuable information on the power of the associated test. In this paper, based on one observation X sampled from a chi-squared distribution with p degrees of freedom and non-centrality parameter [delta], we study a new class of non-centrality parameter estimators , and investigate their statistical properties under the quadratic loss function. Theoretical and simulation studies indicate that generally works well compared with other existing estimators, especially for relatively small and moderate [delta].