Distribution free testing of goodness of fit in a one dimensional parameter space

Leigh A. Roberts

Statistics & Probability Letters, 2015, vol. 99, issue C, 215-222

Abstract: We propose two versions of asymptotically distribution free empirical processes. When a composite null hypothesis contains a family of distributions indexed by a one dimensional parameter space, and when that single parameter is estimated by maximum likelihood, the resulting distribution free goodness of fit tests are simpler than tests applying the Khmaladze transformation. For the Pareto distribution, the process we advocate is especially simple. The theory is illustrated by fitting the Pareto distribution to threshold exceedances of stock returns, and the Weibull distribution to fibre strength data.

Keywords: Brownian bridge; q-projected Brownian motion; Distribution free; Goodness of fit testing; Pareto; Weibull (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (1)

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DOI: 10.1016/j.spl.2015.01.002

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