Parameter estimation of S-distributions with alternating regression.
I-Chun Chou; Harald Martens; Eberhard O. Voit
SORT (2007)
- Volume: 31, Issue: 1, page 55-74
- ISSN: 1696-2281
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topChou, I-Chun, Martens, Harald, and Voit, Eberhard O.. "Parameter estimation of S-distributions with alternating regression.." SORT 31.1 (2007): 55-74. <http://eudml.org/doc/41936>.
@article{Chou2007,
abstract = {We propose a novel 3-way alternating regression (3-AR) method as an effective strategy for the estimation of parameter values in S-distributions from frequency data. The 3-AR algorithm is very fast and performs well for error-free distributions and artificial noisy data obtained as random samples generated from S-distributions, as well as for traditional statistical distributions and for actual observation data. In rare cases where the algorithm does not immediately converge, its enormous speed renders it feasible to select several initial guesses and search settings as an effective countermeasure.},
author = {Chou, I-Chun, Martens, Harald, Voit, Eberhard O.},
journal = {SORT},
keywords = {Funciones de distribución; Estimación paramétrica; Análisis de regresión; alternating regression; parameter estimation; S-distribution; S-system},
language = {eng},
number = {1},
pages = {55-74},
title = {Parameter estimation of S-distributions with alternating regression.},
url = {http://eudml.org/doc/41936},
volume = {31},
year = {2007},
}
TY - JOUR
AU - Chou, I-Chun
AU - Martens, Harald
AU - Voit, Eberhard O.
TI - Parameter estimation of S-distributions with alternating regression.
JO - SORT
PY - 2007
VL - 31
IS - 1
SP - 55
EP - 74
AB - We propose a novel 3-way alternating regression (3-AR) method as an effective strategy for the estimation of parameter values in S-distributions from frequency data. The 3-AR algorithm is very fast and performs well for error-free distributions and artificial noisy data obtained as random samples generated from S-distributions, as well as for traditional statistical distributions and for actual observation data. In rare cases where the algorithm does not immediately converge, its enormous speed renders it feasible to select several initial guesses and search settings as an effective countermeasure.
LA - eng
KW - Funciones de distribución; Estimación paramétrica; Análisis de regresión; alternating regression; parameter estimation; S-distribution; S-system
UR - http://eudml.org/doc/41936
ER -
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