arm.glm | R Documentation |

Combine all-subsets GLMs using the ARM algorithm. Calculate ARM weights for a set of models.

```
arm.glm(object, R = 250, weight.by = c("aic", "loglik"), trace = FALSE)
armWeights(object, ..., data, weight.by = c("aic", "loglik"), R = 1000)
```

`object` |
for |

`...` |
more fitted model objects. |

`R` |
number of permutations. |

`weight.by` |
indicates whether model weights should be calculated with AIC or log-likelihood. |

`trace` |
if |

`data` |
a data frame in which to look for variables for use with prediction. If omitted, the fitted linear predictors are used. |

For each of all-subsets of the “global” model, parameters are estimated
using randomly sampled half of the data. Log-likelihood given the remaining half
of the data is used to calculate AIC weights. This is repeated `R`

times and mean of the weights is used to average all-subsets parameters
estimated using complete data.

`arm.glm`

returns an object of class `"averaging"`

contaning only
“full” averaged coefficients. See `model.avg`

for object
description.

`armWeights`

returns a numeric vector of model weights.

Number of parameters is limited to `floor(nobs(object) / 2) - 1`

.
All-subsets respect marginality constraints.

Kamil Bartoń

Yang, Y. 2001 Adaptive Regression by Mixing.
*Journal of the American Statistical Association* **96**, 574–588.

Yang, Y. 2003 Regression with multiple candidate models: selecting or mixing?
*Statistica Sinica* **13**, 783–810.

`model.avg`

, `par.avg`

`Weights`

for assigning new model weights to an `"averaging"`

object.

Other implementation of ARM algorithm: `arms`

in (archived) package
**MMIX**.

Other kinds of model weights: `BGWeights`

,
`bootWeights`

,
`cos2Weights`

, `jackknifeWeights`

,
`stackingWeights`

.

```
fm <- glm(y ~ X1 + X2 + X3 + X4, data = Cement)
summary(am1 <- arm.glm(fm, R = 15))
mst <- dredge(fm)
am2 <- model.avg(mst, fit = TRUE)
Weights(am2) <- armWeights(am2, data = Cement, R = 15)
# differences are due to small R:
coef(am1, full = TRUE)
coef(am2, full = TRUE)
```

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