Testing the Semiparametric Box-cox Model with the Bootstrap

Accelerated Life Testing Model Building with Box-cox Transformation

In accelerated life testing, the nominal life time is often related to stress levels by an acceleration equation. Three particular models that have been used frequently in the past are the power law model, the Arrhenius model and the Eyring model. In this paper we suggest choosing a model from a model family which includes the three particular models as special cases. This family is deened by a...

Semiparametric Bootstrap Prediction Intervals in time Series

One of the main goals of studying the time series is estimation of prediction interval based on an observed sample path of the process. In recent years, different semiparametric bootstrap methods have been proposed to find the prediction intervals without any assumption of error distribution. In semiparametric bootstrap methods, a linear process is approximated by an autoregressive process. The...

Bootstrap of a Semiparametric Partially Linear Model with Autoregressive Errors

This paper is concerned with a semiparametric partially linear regression model with unknown regression coefficients, an unknown nonparametric function for the non-linear component, and unobservable serially correlated random errors. The random errors are modeled by an autoregressive time series. We show that the distributions of the feasible semiparametric generalized least squares estimator o...

Testing the Box-Cox Parameter for an Integrated Process*

Computing Marginal Effects in the Box–cox Model

This paper considers computation of fitted values and marginal effects in the Box–Cox regression model. Two methods, (1) the ‘‘smearing’’ technique suggested by Duan (see Ref. 10) and (2) direct numerical integration, are examined and compared with the ‘‘naive’’ method often used in econometrics.