Estimation of Weibull distribution shape and scale parameters is accomplished through use of symmetrically located percentiles from a sample. The process requires algebraic solution of two equations derived from the cumulative distribution function. Three alternatives examined are compared for precision and variability with maximum likelihood (MLE) and least squares (LS) estimators. The best percentile estimator (using the 10th and 90th) is inferior to MLE in variability and to one least squares estimator in accuracy and variability to a small degree. However, application of a correction factor related to sample size improves the percentile estimator substantially, making it more accurate than LS.Parameter estimation, Weibull distribution, ...
We compare the small sample performance (in terms of bias and root mean squared error) of the L-mome...
The technique of unbiasing the maximum likelihood estimates of the scale and shape parameters of the...
In this paper, we use the setup proposed by Balakrishnan and Ag-garwala (2000) to compute approximat...
Abstract: Simple estimators of the Weibull shape parameter and any quantile in uncensored samples ar...
Usually, the parameters of a Weibull distribution are estimated by maximum likelihood estimation. To...
This paper examines the estimation comparison of two methods for Weibull parameters, one is the maxi...
For the Weibull distribution the maximum likelihood method does not provide an explicit estimator fo...
© 2017 Elsevier Ltd Unbiased estimation of the Weibull scale parameter using unweighted linear least...
The estimation of the common shape parameter across different Weibull populations is an important an...
OBJECTIVES Comparison of estimation of the two-parameter Weibull distribution by two least squares ...
Among the probability density functions that estimate and project diametric distributions, the Weibu...
© 2017 Elsevier Ltd Confidence limits (at selected levels of 68.27%, 90%, 95% and 99%) for unbiased ...
[[abstract]]This study proposes an alternative to the weighted least-squares (WLS) procedure for est...
The present paper applies a least square method to estimate parameters of a Weibull distribution, wi...
Weibull distributions are widely used in reliability and survival analysis. In this paper, different...
We compare the small sample performance (in terms of bias and root mean squared error) of the L-mome...
The technique of unbiasing the maximum likelihood estimates of the scale and shape parameters of the...
In this paper, we use the setup proposed by Balakrishnan and Ag-garwala (2000) to compute approximat...
Abstract: Simple estimators of the Weibull shape parameter and any quantile in uncensored samples ar...
Usually, the parameters of a Weibull distribution are estimated by maximum likelihood estimation. To...
This paper examines the estimation comparison of two methods for Weibull parameters, one is the maxi...
For the Weibull distribution the maximum likelihood method does not provide an explicit estimator fo...
© 2017 Elsevier Ltd Unbiased estimation of the Weibull scale parameter using unweighted linear least...
The estimation of the common shape parameter across different Weibull populations is an important an...
OBJECTIVES Comparison of estimation of the two-parameter Weibull distribution by two least squares ...
Among the probability density functions that estimate and project diametric distributions, the Weibu...
© 2017 Elsevier Ltd Confidence limits (at selected levels of 68.27%, 90%, 95% and 99%) for unbiased ...
[[abstract]]This study proposes an alternative to the weighted least-squares (WLS) procedure for est...
The present paper applies a least square method to estimate parameters of a Weibull distribution, wi...
Weibull distributions are widely used in reliability and survival analysis. In this paper, different...
We compare the small sample performance (in terms of bias and root mean squared error) of the L-mome...
The technique of unbiasing the maximum likelihood estimates of the scale and shape parameters of the...
In this paper, we use the setup proposed by Balakrishnan and Ag-garwala (2000) to compute approximat...