随机中止试验的线性模型中参数估计的几个性质

When sample size is a sequence of r.v., the parametric estimates in linear models are interesting both theoretically and practically. For linear models Y_i=x_iβ+e_i,i=1,2,…where {e_i} are p-dimensional i .i .d.r.v′.s with Ee₁=0. Var e₁=σ²,0<σ²<∞. we consider estimate σ²(v_n) of error variance σ² and least squares estimate β(v_n) of regression coefficient β, here {v_n} is a sequence of r.v. with positve integers larger than P. In this paper some properties of estimates are discussed . Those are unbiasedness, consistency and normality . For σ²(v_n), we also obtain some orders for convergence to normal distribution.

Some Properties of Parametric Estimates in Linear Models with Randomly Stopped Test