[Forum SIS] DEC (Bocconi) Statistics Seminars - December 1st

[Isadora Antoniano]

We are glad to announce the next:

*DEC - Statistics Seminars*


*Thursday, December 1st*

Bocconi University,
Room 3-E4-SR03
Via Rontgen 1 - 3rd floor

Time: *11:15 am*


* Alejandro Jara *(Pontificia Universidad Catolica de Chile)



*Bayesian nonparametric approaches for the analysis of compositional data
based on Bernstein polynomials*

*Abstract:*We will discuss Bayesian nonparametric procedures for density
estimation and fully nonparametric regression for compositional data, that
is, data supported in a multidimensional simplex. The procedures are based
on modified classes of Bernstein polynomials. We show that the modified
classes retain the well known approximation properties of the classical
versions defined on an hypercube and on a multidimensional simplex. Based
on these classes, we define prior distributions, and study the support and
asymptotic behavior of the posterior distribution under iid sampling.
Finally, novel classes of probability models for sets of
predictor-dependent probability distributions are proposed. Appealing
theoretical properties such as support, continuity, marginal distribution,
correlation structure, and consistency of the posterior distribution are
studied.
(Keywords: Simplex; Random Bernstein polynomials; Dependent Dirichlet
processes)



Time: *12:30 pm*


* Nicola Sartori *(Università degli Studi di Padova)



*Median bias reduction of maximum likelihood estimates*

*Abstract:*

For regular parametric problems, we show how median centering of the
maximum likelihood estimate can be achieved by a simple modification of the
score equation. For a scalar parameter of interest, the estimator is
third-order median unbiased and equivariant under interest respecting
reparameterizations. With a vector parameter of interest, componentwise
equivariance and third-order median centering are obtained. The new method
does not depend on the existence of the maximum likelihood estimate and is
effective in preventing infinite estimates, like Firth’s (1993,
Biometrika) implicit method for bias reduction. Simulation results for
continuous and discrete models, including binary regression, confirm that
the method succeeds in solving the infinite estimate problem and in
achieving componentwise median centering, while keeping comparable
dispersion and the same approximate distribution as its main competitors.
The properties of the method are maintained also in extreme settings,
characterized by large dimensional parameters.
(Joint with E. C. Kenne Pagui and A. Salvan)


The DEC statistics seminars schedule is available at
http://www.unibocconi.eu/statseminar


Kind regards,
*Raffaella Piccarreta and Isadora Antoniano*



*ATTENTION:*

If you are a guest and you do not have a Bocconi ID Card to access to the
Bocconi Buildings, please confirm your participation by sending an email to
simona.gagino a unibocconi.it
In addition, we suggest to print, fill out and send the attached form (to
give your consent to personal data handling) via email to the same address.
In this way, the check-in procedure at the entrance will be faster and
easier.


***************************************************
Isadora Antoniano Villalobos

Assistant Professor
DEC - Department of Decision Sciences,
Bocconi University, via Guglielmo Röntgen 1 (3rd floor, room D1-16). 20136,
Milano.
email: isadora.antoniano a unibocconi.it

Web page: http://faculty.unibocconi.eu/isadoraantonianovillalobos
***************************************************
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