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- Timestamp:
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Mar 30, 2011, 3:50:30 PM (14 years ago)
- Author:
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Víctor de Buen Remiro
- Comment:
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v15
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v16
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89 | 89 | [[LatexEquation( \mu = g^{-1}\left(\eta\right)=\exp\left(\eta\right) )]] [[BR]] [[BR]] |
90 | 90 | * the probability mass function [[BR]] [[BR]] |
91 | | [[LatexEquation( f\left(y;\mu\right)=\frac{1}{y!}e^{-\mu}\mu^{y} )]] |
| 91 | [[LatexEquation( f\left(y;\mu\right)=\frac{1}{y!}e^{-\mu}\mu^{y} )]] [[BR]] [[BR]] |
92 | 92 | * and its logarithm will be [[BR]] [[BR]] |
93 | | [[LatexEquation( \ln f\left(y;\mu\right)=-\ln\left(y!\right)+y\ln\left(\mu\right)-\mu = -\ln\left(y!\right)+y\eta-e^{\eta} )]] |
| 93 | [[LatexEquation( \ln f\left(y;\mu\right)=-\ln\left(y!\right)+y\ln\left(\mu\right)-\mu = -\ln\left(y!\right)+y\eta-e^{\eta} )]] [[BR]] [[BR]] |
94 | 94 | * the partial derivatives of log-density function respect to the linear prediction is [[BR]] [[BR]] |
95 | 95 | [[LatexEquation( \frac{\partial\ln f}{\partial\eta}=y-e^{\eta} )]] [[BR]] [[BR]] |