The Method of Test for Goodness of Fit of Laplace's Distribution

Haruyuki HARADA

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Haruyuki HARADA, "The Method of Test for Goodness of Fit of Laplace's Distribution" in IEICE TRANSACTIONS on transactions, vol. E73-E, no. 6, pp. 864-866, June 1990, doi: .
Abstract: A new method of test for goodness of fit of Laplace's distribution is being proposed in this paper. The new parameter H is defined by the two standard deviations which are estimated by the methods of moments and of maximum likelihood. If the number of data is large, the goodness of the Laplace's distribution is easily tested by the percentile of the normal distribution of the parameter H.
URL: https://globals.ieice.org/en_transactions/transactions/10.1587/e73-e_6_864/_p

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@ARTICLE{e73-e_6_864,
author={Haruyuki HARADA, },
journal={IEICE TRANSACTIONS on transactions},
title={The Method of Test for Goodness of Fit of Laplace's Distribution},
year={1990},
volume={E73-E},
number={6},
pages={864-866},
abstract={A new method of test for goodness of fit of Laplace's distribution is being proposed in this paper. The new parameter H is defined by the two standard deviations which are estimated by the methods of moments and of maximum likelihood. If the number of data is large, the goodness of the Laplace's distribution is easily tested by the percentile of the normal distribution of the parameter H.},
keywords={},
doi={},
ISSN={},
month={June},}

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TY - JOUR
TI - The Method of Test for Goodness of Fit of Laplace's Distribution
T2 - IEICE TRANSACTIONS on transactions
SP - 864
EP - 866
AU - Haruyuki HARADA
PY - 1990
DO -
JO - IEICE TRANSACTIONS on transactions
SN -
VL - E73-E
IS - 6
JA - IEICE TRANSACTIONS on transactions
Y1 - June 1990
AB - A new method of test for goodness of fit of Laplace's distribution is being proposed in this paper. The new parameter H is defined by the two standard deviations which are estimated by the methods of moments and of maximum likelihood. If the number of data is large, the goodness of the Laplace's distribution is easily tested by the percentile of the normal distribution of the parameter H.
ER -