LAUSR.org creates dashboard-style pages of related content for over 1.5 million academic articles. Sign Up to like articles & get recommendations!

Estimating the parameter of selected uniform population under the squared log error loss function

Photo by 20164rhodi from unsplash

ABSTRACT Let π1, …, πk be k (⩾ 2) independent populations, where πi denotes the uniform distribution over the interval (0, θi) and θi > 0 (i = 1, …,… Click to show full abstract

ABSTRACT Let π1, …, πk be k (⩾ 2) independent populations, where πi denotes the uniform distribution over the interval (0, θi) and θi > 0 (i = 1, …, k) is an unknown scale parameter. The population associated with the largest scale parameter is called the best population. For selecting the best population, We use a selection rule based on the natural estimators of θi, i = 1, …, k, for the case of unequal sample sizes. Consider the problem of estimating the scale parameter θL of the selected uniform population when sample sizes are unequal and the loss is measured by the squared log error (SLE) loss function. We derive the uniformly minimum risk unbiased (UMRU) estimator of θL under the SLE loss function and two natural estimators of θL are also studied. For k = 2, we derive a sufficient condition for inadmissibility of an estimator of θL. Using these condition, we conclude that the UMRU estimator and natural estimator are inadmissible. Finally, the risk functions of various competing estimators of θL are compared through simulation.

Keywords: loss function; parameter; parameter selected; population

Journal Title: Communications in Statistics - Theory and Methods
Year Published: 2018

Link to full text (if available)


Share on Social Media:                               Sign Up to like & get
recommendations!

Related content

More Information              News              Social Media              Video              Recommended



                Click one of the above tabs to view related content.