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Inference methods for the positive stable laws, which have no closed form expression for the density functions are developed based on a special quadratic distance using negative moments. Asymptotic properties of the quadratic distance estimator (QDE) are established. The QDE is shown to have asymptotic relative efficiency close to 1 for almost all the… (More)

- Shilpa N Raja, Andrew C K Olson, +8 authors A Paul Alivisatos
- Nano letters
- 2013

A nanoscale, visible-light, self-sensing stress probe would be highly desirable in a variety of biological, imaging, and materials engineering applications, especially a device that does not alter the mechanical properties of the material it seeks to probe. Here we present the CdSe-CdS tetrapod quantum dot, incorporated into polymer matrices via… (More)

- Shilpa N Raja, Andrew C K Olson, +6 authors A Paul Alivisatos
- Proceedings of the National Academy of Sciences…
- 2015

With the availability of nanoparticles with controlled size and shape, there has been renewed interest in the mechanical properties of polymer/nanoparticle blends. Despite the large number of theoretical studies, the effect of branching for nanofillers tens of nanometers in size on the elastic stiffness of these composite materials has received limited… (More)

Goodness of fit test procedures for the zeta parametric family based on quadratic distances and the Box--Cox transform are developed. Test statistics based on quadratic distances are shown to follow a chi-square distribution asymptotically. Test procedures based on the Box-Cox transform make use of the estimator of the parameter introduced by the Box-Cox… (More)

- Louis G. Doray, Shu Mei Jiang, Andrew Luong
- Communications in Statistics - Simulation and…
- 2009

In this paper, we develop a method to estimate the two parameters of the discrete stable distribution. By minimizing the quadratic distance between transforms of the empirical and theoretical probability generating functions, we obtain estimators simple to calculate, asymptotically unbiased and normally distributed. We also derive the expression for their… (More)

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