Testing linearity using power transforms of regressors

SEQUENTIALLY TESTING POLYNOMIAL MODEL HYPOTHESES USING POWER TRANSFORMS OF REGRESSORS By

We provide a methodology for testing a polynomial model hypothesis by extending the approach and results of Baek, Cho, and Phillips (2015; BCP) that tests for neglected nonlinearity using power transforms of regressors against arbitrary nonlinearity. We examine and generalize the BCP quasi-likelihood ratio test dealing with the multifold identification problem that arises under the null of the ...

Linearity Testing Using Local Polynomial Approximation

Testing Conditional Independence using Conditional Martingale Transforms

This paper investigates testing conditional independence between Y and Z given λθ(X) for some θ ∈ Θ ⊂ R, for a function λθ(·) known upto a parameter θ ∈ Θ. First, the paper proposes a new method of conditional martingale transforms under which tests are asymptotically pivotal and asymptotically unbiased against √ n-converging Pitman local alternatives. Second, the paper performs an analysis of ...

Testing the assumption of Linearity

The assumption of linearity is tested using five statistical tests for the US and the Canadian unemployment rates. An AR(p) model was used to remove any linear structure from the series. Strong evidence in favour of non−linearity was found in the case of Canada. The result for the US is not so clear cut. The author would like to thank Chung−Ming Kuan, David Chappell, Chris Martin and Costas Mil...

Linearity Testing of A/D Converters Using Selective Code Measurement

Measurement of integral non-linearity (INL) and differential non-linearity (DNL) of an A/D converter using the histogram method incurs large test time. This test time can be a significant percentage of the total test time, especially for high resolution and low sampling-speed A/D converters. This paper describes a test methodology for measuring the INL and DNL specifications of A/D converters b...