-
作者：PIKOUNIS, VB; RAO, PV
作者单位：State University System of Florida; University of Florida
摘要：In a two-sample setting, a two-parameter mixture model is postulated for the treated patients where a proportion of the patients improve and the remaining proportion of nonresponders behave like the control patients. The response is subject to random censoring. Censored data versions of linear rank statistics are developed in order to detect improvement due to treatment. The tests are compared to standard tests such as the log-rank test in terms of asymptotic relative efficiency, empirical pow...
-
作者：WELLS, MT
作者单位：Cornell University
摘要：Cox's proportional hazards model assumes that the duration hazard rate factors into a product of a baseline hazard rate and a nonnegative function of explanatory variables. An estimate of the baseline hazard rate, hence also of overall hazard rate, is proposed, based on a smoothing procedure using a kernel function. It is shown that the proposed estimator is uniformly consistent and converges weakly to a Gaussian process. Bandwidth selection issues are also discussed.
-
作者：MONTI, AC
摘要：This note proposes a test of goodness of fit for time series models based on the sum of the squared residual partial autocorrelations. The test statistic is asymptotically chi(2). Its small-sample performance is studied through a Monte Carlo experiment. It appears sensitive to erroneous specifications especially when the fitted model understates the order of the moving average component.
-
作者：KOENKER, R; NG, P; PORTNOY, S
作者单位：University of Houston System; University of Houston; University of Illinois System; University of Illinois Urbana-Champaign
摘要：Although nonparametric regression has traditionally focused on the estimation of conditional mean functions, nonparametric estimation of conditional quantile functions is often of substantial practical interest. We explore a class of quantile smoothing splines, defined as solutions to [GRAPHICS] with p(tau)(u)= u{tau - I(u < 0)}, p greater than or equal to 1, and appropriately chosen g. For the particular choices p = 1 and p = infinity we characterise solutions (g) over cap as splines, and dis...
-
作者：TSAI, CL
摘要：The Newton-Raphson and Fisher scoring iteratively reweighted least squares methods are two fundamental tools for computing parameter estimators and deletion diagnostics. Jorgensen (1993) proposed a modified method to compute deletion diagnostics. In this paper, we study the relationship between Jorgensen's, Newton-Raphson and Fisher scoring one-step deletion estimators by using the observed and expected Fisher information matrices. In addition, we extend Jorgensen's true leverage and approxima...
