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- Timestamp:
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Mar 30, 2011, 2:18:59 PM (14 years ago)
- Author:
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Víctor de Buen Remiro
- Comment:
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v6
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v7
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25 | 25 | * [[LatexEquation( \eta=X\beta\in\mathbb{R}^{n} )]] the linear prediction |
26 | 26 | * [[LatexEquation( g )]] the link function |
| 27 | * [[LatexEquation( g^-1 )]] the inverse-link or mean function |
27 | 28 | * [[LatexEquation( f)]] the density function of a distribution of the |
28 | 29 | [http://en.wikipedia.org/wiki/Exponential_family exponential family] |
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35 | 36 | The density function becomes as a real valuated function of at least two parameters |
36 | 37 | |
37 | | [[LatexEquation( f\left(y_{k};\mu_{k}\right) )]] |
| 38 | [[LatexEquation( f\left(y;\mu\right) )]] |
38 | 39 | |
39 | | the output [[LatexEquation( y_k )]] and the average |
| 40 | For each row [[LatexEquation( k=1 \dots n)]] we will know the output [[LatexEquation( y_k )]] |
| 41 | and the average |
40 | 42 | |
41 | 43 | [[LatexEquation( \mu_{k}=g^{-1}\left(\eta_{k}\right)=g^{-1}\left(x_{k}\beta\right) )]] |
42 | 44 | |
43 | | for each row [[LatexEquation( k=1 \dots n)]]: |
| 45 | Each particular distribution may have its own additional parameters. |
44 | 46 | |
45 | | This class also implements |
| 47 | This class also implements these common features |
46 | 48 | * scalar prior information of type normal or uniform, truncated or not in both cases, and |
47 | 49 | * linear constraining inequations over linear parameters [[BR]][[BR]] |
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53 | 55 | There is a sample of use in [source:/tolp/OfficialTolArchiveNetwork/GrzLinModel/test/test_0001/test.tol test_0001/test.tol] |
54 | 56 | |
| 57 | In this case we have |
| 58 | |
| 59 | * the identity as link function and mean function [[BR]] [[BR]] |
| 60 | [[LatexEquation( \eta = g\left(\mu\right)= \mu = g^{-1}\left(\eta\right) = \eta)]] [[BR]] [[BR]] |
| 61 | * the density function has the variance as extra parameter[[BR]] [[BR]] |
| 62 | [[LatexEquation( f\left(y;\mu, \sigma^2 \right) ) = \frac{1}{\sqrt{2\pi\sigma^{2}}}e^{^{-\frac{1}{2}\frac{\left(y-\mu\right)^{2}}{\sigma^{2}}}} )]] |
| 63 | |
| 64 | |
55 | 65 | === Weighted Poisson Regresion === |
56 | 66 | |
57 | 67 | It will be implemented in [source:/tolp/OfficialTolArchiveNetwork/GrzLinModel/WgtPoisson.tol GrzLinModel::@WgtPoisson] but is not available yet. |
| 68 | |
| 69 | In this case we have |
| 70 | |
| 71 | * the link function [[BR]] [[BR]] |
| 72 | [[LatexEquation( \eta g\left(\mu\right)=\ln\left(\mu\right) )]] [[BR]] [[BR]] |
| 73 | * the mean function [[BR]] [[BR]] |
| 74 | [[LatexEquation( \mu = g^{-1}\left(\eta\right)=\exp\left(\eta\right) )]] [[BR]] [[BR]] |
| 75 | * the probability mass function [[BR]] [[BR]] |
| 76 | [[LatexEquation( f\left(y;\mu \right) ) = \frac{1}{y!}e^{-\mu}\mu^{y} )]] |
| 77 | |
58 | 78 | |
59 | 79 | === Weighted Qualitative Regresion === |