Template:Mixed weibull MLE: Difference between revisions
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The same space of parameters, namely <math>\widehat{{{\rho }_{1,\text{ }}}}</math> <math>\widehat{{{\beta }_{1}}},</math> <math>\widehat{{{\eta }_{1}}},</math> <math>\widehat{{{\rho }_{2,\text{ }}}}\widehat{{{\beta }_{2}}},</math> <math>\widehat{{{\eta }_{2}}},...,</math> <math>\widehat{{{\rho }_{S,}}\text{ }}\widehat{{{\beta }_{S}}},</math> <math>\widehat{{{\eta }_{S}}},</math> is also used under the MLE method, using the likelihood function as given in Appendix C of this reference. Weibull++ uses the EM algorithm, short for Expectation-Maximization algorithm, for the MLE analysis. Details on the numerical procedure are beyond the scope of this reference. | The same space of parameters, namely <math>\widehat{{{\rho }_{1,\text{ }}}}</math> <math>\widehat{{{\beta }_{1}}},</math> <math>\widehat{{{\eta }_{1}}},</math> <math>\widehat{{{\rho }_{2,\text{ }}}}\widehat{{{\beta }_{2}}},</math> <math>\widehat{{{\eta }_{2}}},...,</math> <math>\widehat{{{\rho }_{S,}}\text{ }}\widehat{{{\beta }_{S}}},</math> <math>\widehat{{{\eta }_{S}}},</math> is also used under the MLE method, using the likelihood function as given in Appendix C of this reference. Weibull++ uses the EM algorithm, short for Expectation-Maximization algorithm, for the MLE analysis. Details on the numerical procedure are beyond the scope of this reference. |
Revision as of 17:27, 14 February 2012
MLE
The same space of parameters, namely [math]\displaystyle{ \widehat{{{\rho }_{1,\text{ }}}} }[/math] [math]\displaystyle{ \widehat{{{\beta }_{1}}}, }[/math] [math]\displaystyle{ \widehat{{{\eta }_{1}}}, }[/math] [math]\displaystyle{ \widehat{{{\rho }_{2,\text{ }}}}\widehat{{{\beta }_{2}}}, }[/math] [math]\displaystyle{ \widehat{{{\eta }_{2}}},..., }[/math] [math]\displaystyle{ \widehat{{{\rho }_{S,}}\text{ }}\widehat{{{\beta }_{S}}}, }[/math] [math]\displaystyle{ \widehat{{{\eta }_{S}}}, }[/math] is also used under the MLE method, using the likelihood function as given in Appendix C of this reference. Weibull++ uses the EM algorithm, short for Expectation-Maximization algorithm, for the MLE analysis. Details on the numerical procedure are beyond the scope of this reference.