23,129 research outputs found
ESTIMATING NON-PARAMETRIC AND PARAMETRIC TRANSFORMATION FUNCTIONS FROM SURVEY DATA: AN APPLICATION OF MINIMUM CROSS-ENTROPY
A model of a (convex) technology of representative and non-representative firms in a heterogeneous sector is presented in non-parametric and parametric versions. The heterogeneity is specified with error terms. The models including a non-parametric distribution of the errors can be estimated with entropy econometrics from firm survey data. This requires two important modifications in the standard approach to entropy estimation of Golan, Judge and Miller: The compact support of the probability distribution should be designed to capture eventual non-zero covariance. And cross-entropy need to be redefined for cases of multiple observations.Research Methods/ Statistical Methods,
Maximum Entropy Estimation of the Galactic Bulge Morphology via the VVV Red Clump
The abundance and narrow magnitude dispersion of Red Clump (RC) stars make
them a popular candidate for mapping the morphology of the bulge region of the
Milky Way. Using an estimate of the RC's intrinsic luminosity function, we
extracted the three-dimensional density distribution of the RC from deep
photometric catalogues of the VISTA Variables in the Via Lactea (VVV) survey.
We used maximum entropy based deconvolution to extract the spatial distribution
of the bulge from Ks-band star counts. We obtained our extrapolated
non-parametric model of the bulge over the inner 40 by 40 degrees squared
region of the Galactic centre. Our reconstruction also naturally matches onto a
parametric fit to the bulge outside the VVV region and inpaints overcrowded and
high extinction regions. We found a range of bulge properties consistent with
other recent investigations based on the VVV data. In particular, we estimated
the bulge mass to be in the range 13 to 17 billion solar masses, the
X-component to be between 18% and 25% of the bulge mass, and the bulge angle
with respect to the Sun-Galactic centre line to be between 18 and 32 degrees.
Studies of the Fermi Large Area Telescope (LAT) gamma-ray Galactic centre
excess suggests that the excess may be traced by Galactic bulge distributed
sources. We applied our deconvolved density in a template fitting analysis of
this Fermi-LAT GeV excess and found an improvement in the fit compared to
previous parametric based templates.Comment: 25 pages, 27 figures, minor typo correcte
Efficient and robust estimation for financial returns: an approach based on q-entropy
We consider a new robust parametric estimation procedure, which minimizes an empirical version of the Havrda-Charvà t-Tsallis entropy. The resulting estimator adapts according to the discrepancy between the data and the assumed model by tuning a single constant q, which controls the trade-off between robustness and effciency. The method is applied to expected return and volatility estimation of financial asset returns under multivariate normality. Theoretical properties, ease of implementability and empirical results on simulated and financial data make it a valid alternative to classic robust estimators and semi-parametric minimum divergence methods based on kernel smoothing.q-entropy; robust estimation; power-divergence; financial returns
Efficient and robust estimation for financial returns: an approach based on q-entropy
We consider a new robust parametric estimation procedure, which minimizes an empirical version of the Havrda-Charv_at-Tsallis entropy. The resulting estimator adapts according to the discrepancy between the data and the assumed model by tuning a single constant q, which controls the trade-o_ between robustness and e_ciency. The method is applied to expected re- turn and volatility estimation of _nancial asset returns under multivariate normality. Theoretical properties, ease of implementability and empirical re- sults on simulated and _nancial data make it a valid alternative to classic robust estimators and semi-parametric minimum divergence methods based on kernel smoothingq-entropy, robust estimation, power-divergence, _nancial returns
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