(2011), Further simulation evidence on the performance of the Poisson pseudo-maximum likelihood estimator, Economics Letters 112(2), 220- 222.Tenreyro, Silvana, "Further simulation evidence on the performance of the Poisson pseudo-maximum likelihood estimator," Economics Letters, 2009, 44 (0), ...
For a certain failure of the assumptions, namely the equidispersion restriction, the Poisson maximum likelihood estimator remains consistent. However, the estimated asymptotic covariance matrix based on (18) or (19) may miss-estimate the appropriate matrix. An estimator based on both (18) and (19...
simulationIn a model of equioverlapping samples maximum likelihood estimation of a Poisson parameter is examined and compared with two linear unbiased estimations by mean squared error. Since a likelihood estimator is not explicitly available in general, a simulation study has been performed and the ...
The maximum likelihood estimator (MLE) suffers from the instability problem in the presence of multicollinearity for a Poisson regression model (PRM). In this study, we propose a new estimator with some biasing parameters to estimate the regression coefficients for the PRM when there is multicollinea...
We give a necessary and sufficient condition on the coefficients of the linear function for the maximum likelihood estimator (MLE) which satisfies the order restriction to dominate the unbiased estimator under squared error loss. Furthermore, simultaneous estimation of two ordered Poisson means is ...
The Maximum Likelihood Estimator (MLE) is used to estimate the model parameters in PRMs. However, the MLE may suffer from various drawbacks that arise due to the existence of multicollinearity problems. Many estimators have been proposed as alternatives to each other to alleviate the ...
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Stata cpoisson - 被限制的泊松回归命令的中文名称说明书 Title stata.com cpoisson—Censored Poisson regression Description Quick start Menu Syntax Options Remarks and examples Stored results Methods and formulas References Also see Description cpoissonfits a Poisson model of a count dependent variable ...
We showed that the Anderson–Darling estimator is the most efficient for estimating the parameters of the proposed distribution. Our proposed methodology was also illustrated in three real data sets related to the minimum, average and the maximum flows during October at So Carlos River in Brazil ...
maximum likelihood estimatormean squared errorIn order to combat multicollinearity, the r – d class estimator was introduced in linear and binary logistic regression models. Since the generalized linear models (GLMs) are the models that include logistic regression model, Poisson regression model, etc....