Some Unified Results on Isotonic Regression Estimators of Order Restricted Parameters of a General Bivariate Location/Scale Model

preprint2022arXivOpen access

Abstract

We consider component-wise estimation of order restricted location/scale parameters θ1θ_1 and θ2θ_2 (θ1≤θ2θ_1\leq θ_2) of a general bivariate distribution under the squared error loss function. To find improvements over the best location/scale equivariant estimators (BLEE/BSEE) of θ1θ_1 and θ2θ_2, we study isotonic regression of suitable location/scale equivariant estimators (LEE/SEE) of θ1θ_1 and θ2θ_2 with general weights. Let D1,ν\mathcal{D}_{1,ν} and D2,β\mathcal{D}_{2,β} denote suitable classes of isotonic regression estimators of θ1θ_1 and θ2θ_2, respectively. Under the squared error loss function, we characterize admissible estimators within classes D1,ν\mathcal{D}_{1,ν} and D2,β\mathcal{D}_{2,β}, and identify estimators that dominate the BLEE/BSEE of θ1θ_1 and θ2θ_2. Our study unifies and extends several studies reported in the literature for specific probability distributions having independent marginals. Additionally, some new and interesting results are obtained. A simulation study is also considered to compare the risk performances of various estimators.

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