|Budget Amount *help
¥1,000,000 (Direct Cost : ¥1,000,000)
Fiscal Year 1999 : ¥400,000 (Direct Cost : ¥400,000)
Fiscal Year 1998 : ¥600,000 (Direct Cost : ¥600,000)
We considered two-sample and multivariate two-way manova model included in YィイD2iィエD2=h(xィイD2iィエD2,θ) + εィイD2iィエD2, i=1,・・・, n,θ∈Θ where εィイD2iィエD2, i=1, ・・・, n, are mutually independent and identically distributed with a p-variate continuous distribution function F(x,Σ) having null mean and finite positive definite variance-covariance matrix Σ. In pratical applicational model assumptions, the scale-parameter of the underlying distribution is unknown and Fisher's consistency does not hold. We need to construct flexible statistical procedures. So scale invariant statistical procedures based on M-statistics were proposed. Their asymptotic noncentral xィイD12ィエD1-distributions for testing homogeneity were drawn under a contiguous sequence of location-alternatives without assuming Fisher consistency : ∫ψィイD2lィエD2(xィイD1(l)ィエD1)dFィイD2lィエD2(xィイD1(l)ィエD1)=0. Asymptotic robustness was derived. The permutation tests based on the proposed M-test statistics were considered. Using a Monte Carlo simulation, their power was compared with permutation tests based on parametric test statistics. Next robust estimators for location parameters were proposed, based on studentized M-statistics. The asymptotic normality of these estimators was drawn. After a simple algorithm was studied, the risks of the M-estimators and the least squares estimators were compared due to a simulation. For a univariate case, it was found that (i) the asymptotic relative efficiency (ARE) of the proposed M-procedures relative to parametric procedures agreed with the ARE of one-sample M-estimator proposed by Huber (1964) relative to the sample mean, and that (ii) for small sample sizes, the M-procedures were more efficient than parametric procedures except the case that an underlying distribution is normal.
Moreover many computer soft programs were created and shrinkage estimators were discussed.