Title of article :
Improved maximum likelihood estimation of parameters in the Maxwell distribution
Author/Authors :
Maghami, Mohammad Mahdi Department of Statistics - University of Isfahan, Isfahan, Iran , Bahrami, Mohammad Department of Statistics - University of Isfahan, Isfahan, Iran
Abstract :
Maximum likelihood estimators are usually biased. The first order bias
term of the maximum likelihood estimators can be large for a small or medium sample
size, and this bias may have a significant effect on distribution performance. Different
methods may be used to reduce this bias. These methods have inspired many scholars
to study this field over the past years, but the use of Bartlett’s method requires the
expected value of third power derivatives of the likelihood function. Consequently,
because this quantity (the expected value of third power derivatives of the likelihood
function) is not necessarily calculable in some distributions, in this paper we propose
a new method based on algebraic approximation of the maximum likelihood estimator
bias which needless the expected value of third power derivatives of the likelihood function.
In addition, as an application of this method, we will consider a bias correction
for estimating parameters of Maxwell distribution.
Keywords :
Bias-corrected estimators , Bias prevention , Maximum likelihood estimator , Two-parameter Maxwell distribution
Journal title :
Journal of Statistical Modelling: Theory and Applications (JSMTA)