Package ‘MuMIn’

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22 merge.model.selection Details Mallows’ Cp statistic is the residual deviance plus twice the estimate of σ 2 times the residual degrees of freedom. It is closely related to AIC (and a multiple of it if the dispersion is known). ICOMP (I for informational and COMP for complexity) penalizes the covariance complexity of the model, rather than the number of parameters directly. CAICF (C is for ‘consistent’ and F denotes the use of the Fisher information matrix) includes with penalty the natural logarithm of the determinant of the estimated Fisher information matrix. Value If just one object is provided, the functions return a numeric value with the corresponding IC; otherwise a data.frame with rows corresponding to the objects is returned. References Mallows, C. L. (1973) Some comments on Cp. Technometrics 15: 661–675. Bozdogan, H. and Haughton, D.M.A. (1998) Information complexity criteria for regression models. Comp. Stat. & Data Analysis 28: 51-76. Anderson, D. R. and Burnham, K. P. (1999) Understanding information criteria for selection among capture-recapture or ring recovery models. Bird Study 46: 14–21. Spiegelhalter, D.J., Best, N.G., Carlin, B.R., van der Linde, A. (2002) Bayesian measures of model complexity and fit. Journal of the Royal Statistical Society Series B-Statistical Methodology 64: 583–616. See Also AIC and BIC in stats, AICc. QIC for GEE model selection. extractDIC in package arm, on which the (non-visible) method extractDIC.merMod used by DIC is based. merge.model.selection Combine model selection tables Description Combine two or more model selection tables. Usage ## S3 method for class model.selection merge(x, y, suffixes = c(".x", ".y"), ...) ## S3 method for class model.selection rbind(..., deparse.level = 1, make.row.names = TRUE)
merge.model.selection 23 Arguments x, y, ... model.selection objects to be combined. (. . . ignored in merge) suffixes a character vector with two elements that are appended respectively to row names of the combined tables. make.row.names logical indicating if unique and valid row.names should be constructed from the arguments. deparse.level ignored. Value A "model.selection" object containing models from all provided tables. Note Both ∆ IC values and Akaike weights are recalculated in the resulting tables. Models in the combined model selection tables must be comparable, i.e. fitted to the same data, however only very basic checking is done to verify that. The models must also be ranked by the same information criterion. Unlike the merge method for data.frame, this method appends second table to the first (similarly to rbind). Author(s) Kamil Bartoń See Also dredge, model.sel, merge, rbind. Examples ## Not run: require(mgcv) ms1
Page 1 and 2: Type Package Title Multi-Model Infe
Page 3 and 4: MuMIn-package 3 model.avg calculate
Page 5 and 6: arm.glm 5 See Also Akaike’s An In
Page 7 and 8: Beetle 7 Beetle Flour beetle mortal
Page 9 and 10: Cement 9 print(tab, digits = 3, na.
Page 11 and 12: dredge 11 varying extra x Details a
Page 13 and 14: dredge 13 Value Note ‘*nvar*‘ n
Page 15 and 16: exprApply 15 # Add other informatio
Page 17 and 18: Formula manipulation 17 # submodels
Page 19 and 20: GPA 19 See Also dredge and pdredge,
Page 21: Information criteria 21 importance(
Page 25 and 26: model.avg 25 full, adjust.se logica
Page 27 and 28: model.avg 27 coef, vcov, confint an
Page 29 and 30: model.sel 29 # (in this case it doe
Page 31 and 32: model.selection.object 31 model.sel
Page 33 and 34: nested 33 Note • spml* (if fitted
Page 35 and 36: par.avg 35 Examples fm
Page 37 and 38: pdredge 37 Arguments Details Value
Page 39 and 40: plot.model.selection 39 modSel(fitL
Page 41 and 42: predict.averaging 41 Details predic
Page 43 and 44: QAIC 43 Description Calculate a mod
Page 45 and 46: QIC 45 Arguments Value Note object
Page 47 and 48: .squaredLR 47 Author(s) This implem
Page 49 and 50: std.coef 49 See Also summary.lm, r.
Page 51 and 52: stdize 51 stdize Standardize data D
Page 53 and 54: stdize 53 Value stdize returns a ve
Page 55 and 56: subset.model.selection 55 ## S3 met
Page 57 and 58: updateable 57 x an object from whic
Page 59 and 60: Weights 59 ### ## Not run: # "lmeki
Page 61 and 62: Index ∗Topic datasets Beetle, 7 C
Page 63: INDEX 63 negbin, 32 nested, 33 null

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