Model Specification Tests Based on Artificial Linear Regressions

mortality forecasting based on lee-carter model

over the past decades a number of approaches have been applied for forecasting mortality. in 1992, a new method for long-run forecast of the level and age pattern of mortality was published by lee and carter. this method was welcomed by many authors so it was extended through a wider class of generalized, parametric and nonlinear model. this model represents one of the most influential recent d...

Consistent model-specification tests based on parametric bootstrap

In this paper we establish consistent tests of L2-type for the parametric functional form of the conditional mean of time series with values in Rd. A recent result on asymptotic distributions of U -statistics of weakly dependent observations is invoked to obtain the limit distributions of the test statistics. Since the asymptotic distributions depend on unknown parameters in a complicated way, ...

Some Specification Tests for the Linear Regression Model

Artificial Regressions

Associated with every popular nonlinear estimation method is at least one “artificial” linear regression. We define an artificial regression in terms of three conditions that it must satisfy. Then we show how artificial regressions can be useful for numerical optimization, testing hypotheses, and computing parameter estimates. Several existing artificial regressions are discussed and are shown ...

On model-free conditional coordinate tests for regressions

Existing model-free tests of the conditional coordinate hypothesis in sufficient dimension reduction (Cook (1998) [3]) focused mainly on the first-order estimation methods such as the sliced inverse regression estimation (Li (1991) [14]). Such testing procedures based on quadratic inference functions are difficult to be extended to second-order sufficient dimension reduction methods such as the...