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/dports/math/R-cran-car/car/man/
H A DdfbetaPlots.Rd4 \alias{dfbetaPlots.lm}
5 \alias{dfbetasPlots.lm}
8 \title{dfbeta and dfbetas Index Plots}
10 These functions display index plots of dfbeta (effect on coefficients of deleting
22 \method{dfbetaPlots}{lm}(model, terms= ~ ., intercept=FALSE, layout=NULL, ask,
23 main, xlab, ylab, labels=rownames(dfbeta),
28 \method{dfbetasPlots}{lm}(model, terms=~., intercept=FALSE, layout=NULL, ask,
36 \item{model}{model object produced by \code{lm} or \code{glm}.
39 One dfbeta or dfbetas plot is drawn for each regressor. The default
88 \seealso{\code{\link{dfbeta}} ,\code{\link{dfbetas}}}
[all …]
H A DinfIndexPlot.Rd4 \alias{infIndexPlot.lm}
17 \method{infIndexPlot}{lm}(model, vars=c("Cook", "Studentized", "Bonf", "hat"),
21 vars = c("dfbeta", "dfbetas", "var.cov.comps",
24 vars = c("dfbeta", "dfbetas", "var.cov.comps",
28 …\item{model}{A regression object of class \code{lm}, \code{glm}, or \code{lmerMod}, or an influence
30 …\code{\link{influence.mixed.models}}). The \code{"lmerMod"} method calls the \code{"lm"} method an…
36 linear model, or \code{"dfbeta"}, \code{"dfbetas"}, \code{"var.cov.comps"}, and
38 All but \code{"dfbeta"} and \code{"dfbetas"} may be abbreviated by the first one or more letters.
71 influenceIndexPlot(lm(prestige ~ income + education + type, Duncan))
/dports/math/R/R-4.1.2/src/library/stats/man/
H A Dinfluence.measures.Rd22 \alias{hatvalues.lm}
24 \alias{rstandard.lm}
27 \alias{rstudent.lm}
29 \alias{dfbeta}
30 \alias{dfbeta.lm}
32 \alias{dfbetas.lm}
42 \method{rstandard}{lm}(model, infl = lm.influence(model, do.coef = FALSE),
55 dfbeta(model, \dots)
56 \method{dfbeta}{lm}(model, infl = lm.influence(model, do.coef = TRUE), \dots)
149 For \code{hatvalues}, \code{dfbeta}, and \code{dfbetas}, the method
[all …]
/dports/math/libRmath/R-4.1.1/src/library/stats/man/
H A Dinfluence.measures.Rd22 \alias{hatvalues.lm}
24 \alias{rstandard.lm}
27 \alias{rstudent.lm}
29 \alias{dfbeta}
30 \alias{dfbeta.lm}
32 \alias{dfbetas.lm}
42 \method{rstandard}{lm}(model, infl = lm.influence(model, do.coef = FALSE),
55 dfbeta(model, \dots)
56 \method{dfbeta}{lm}(model, infl = lm.influence(model, do.coef = TRUE), \dots)
149 For \code{hatvalues}, \code{dfbeta}, and \code{dfbetas}, the method
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/dports/math/R-cran-VGAM/VGAM/R/
H A Dmodel.matrix.vglm.q876 dfbeta <- matrix(0, n.lm, p.vlm) functionVar
913 dfbeta[ii, ] <- coef.model - fit$coeff
917 dimnames(dfbeta) <- list(rownames(X.lm), names(coef.model))
918 dfbeta
926 setMethod("dfbeta", "matrix", function(model, ...) method
930 setMethod("dfbeta", "vlm", function(model, ...) method
932 setMethod("dfbeta", "vglm", function(model, ...) method
936 setMethod("dfbeta", "rrvglm", function(model, ...) method
938 setMethod("dfbeta", "qrrvglm", function(model, ...) method
940 setMethod("dfbeta", "rrvgam", function(model, ...) method
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/dports/math/R-cran-car/car/
H A DNAMESPACE8 S3method(Confint, lm)
17 S3method(S, lm)
26 S3method(print, S.lm)
35 S3method(brief, lm)
40 S3method(Predict, lm)
56 # S3method(dfbeta, influence.merMod)
57 S3method(dfbeta, influence.lme)
82 cov, cov.wt, cov2cor, density, deviance, df.residual, dfbeta, dnorm,
307 S3method(hccm, lm)
337 S3method(mmp, lm)
[all …]
/dports/math/R/R-4.1.2/tests/
H A Dlm-tests.R8 roller.lmu <- lm(weight~depression, data=roller)
13 roller.lm <- lm(weight~depression, data=roller, weights= 1:10)
14 roller.lm0 <- lm(weight~depression, data=roller, weights= 0:9)
15 roller.lm9 <- lm(weight~depression, data=roller[-1,],weights= 1:9)
65 lm.SR <- lm(sr ~ pop15 + pop75 + dpi + ddpi, data = LifeCycleSavings)
71 signif(dfbeta(lm.SR), 3)
90 mlmfit <- lm(reacttime ~ 1)
H A Dlm-tests.Rout.save30 > roller.lm <- lm(weight~depression, data=roller, weights= 1:10)
56 > all.equal(deviance(roller.lm),
100 > all.equal(rstudent(roller.lm),
103 > all.equal(cooks.distance(roller.lm),
125 > lm.SR <- lm(sr ~ pop15 + pop75 + dpi + ddpi, data = LifeCycleSavings)
126 > (IM <- influence.measures(lm.SR))
250 > signif(dfbeta(lm.SR), 3)
302 > covratio (lm.SR)
340 > mlmfit <- lm(reacttime ~ 1)
346 lm(formula = reacttime ~ 1) :
[all …]
/dports/math/libRmath/R-4.1.1/tests/
H A Dlm-tests.R8 roller.lmu <- lm(weight~depression, data=roller)
13 roller.lm <- lm(weight~depression, data=roller, weights= 1:10)
14 roller.lm0 <- lm(weight~depression, data=roller, weights= 0:9)
15 roller.lm9 <- lm(weight~depression, data=roller[-1,],weights= 1:9)
65 lm.SR <- lm(sr ~ pop15 + pop75 + dpi + ddpi, data = LifeCycleSavings)
71 signif(dfbeta(lm.SR), 3)
90 mlmfit <- lm(reacttime ~ 1)
H A Dlm-tests.Rout.save30 > roller.lm <- lm(weight~depression, data=roller, weights= 1:10)
56 > all.equal(deviance(roller.lm),
100 > all.equal(rstudent(roller.lm),
103 > all.equal(cooks.distance(roller.lm),
125 > lm.SR <- lm(sr ~ pop15 + pop75 + dpi + ddpi, data = LifeCycleSavings)
126 > (IM <- influence.measures(lm.SR))
250 > signif(dfbeta(lm.SR), 3)
302 > covratio (lm.SR)
340 > mlmfit <- lm(reacttime ~ 1)
346 lm(formula = reacttime ~ 1) :
[all …]
/dports/math/R-cran-VGAM/VGAM/man/
H A Dhatvalues.Rd20 %\alias{hatvalues.lm}
25 %\alias{rstandard.lm}
28 %\alias{rstudent.lm}
30 \alias{dfbeta}
33 %\alias{dfbetas.lm}
37 %\alias{cooks.distance.lm}
109 % \code{\link{lm.influence}} or \code{\link{influence}} (the latter
188 % measures (from \code{\link{lm.influence}} or the generic
211 % For \code{hatvalues}, \code{dfbeta}, and \code{dfbetas}, the method
H A Dundocumented-methods.Rd249 \alias{attrassign,lm-method}
360 \alias{dfbeta,ANY-method}
361 \alias{dfbeta,matrix-method}
362 \alias{dfbeta,vlm-method}
363 \alias{dfbeta,vglm-method}
364 \alias{dfbeta,rrvgam-method}
365 \alias{dfbeta,qrrvglm-method}
366 \alias{dfbeta,rcim-method}
367 \alias{dfbeta,rrvglm-method}
/dports/math/R/R-4.1.2/src/library/stats/
H A DNAMESPACE28 df.residual, dfbeta, dfbetas, dffits, dgamma, dgeom, dhyper,
41 knots, ksmooth, lag, lag.plot, line, lm, lm.fit, .lm.fit,
42 lm.influence, lm.wfit, loadings, loess, loess.control,
98 model.matrix.lm, plot.ts, predict.glm, predict.lm,
119 S3method(add1, lm)
128 S3method(alias, lm)
152 S3method(anova, lm)
202 S3method(dfbeta, lm)
317 S3method(nobs, lm)
330 S3method(plot, lm)
[all …]
/dports/math/libRmath/R-4.1.1/src/library/stats/
H A DNAMESPACE28 df.residual, dfbeta, dfbetas, dffits, dgamma, dgeom, dhyper,
41 knots, ksmooth, lag, lag.plot, line, lm, lm.fit, .lm.fit,
42 lm.influence, lm.wfit, loadings, loess, loess.control,
98 model.matrix.lm, plot.ts, predict.glm, predict.lm,
119 S3method(add1, lm)
128 S3method(alias, lm)
152 S3method(anova, lm)
202 S3method(dfbeta, lm)
317 S3method(nobs, lm)
330 S3method(plot, lm)
[all …]
/dports/math/R-cran-lme4/lme4/
H A DNAMESPACE16 deviance, dfbeta, dfbetas,
19 hatvalues, influence, lm, logLik, model.extract, model.frame,
267 S3method(dfbeta,influence.merMod)
/dports/math/R-cran-robustbase/robustbase/tests/
H A DNAcoef.Rout.save20 > ## -- what would have to be done if class "lm" was added.
21 > ## -- general compatibility to class lm.
44 > cm0 <- lm (y ~ x1*x2 + x3, data)
45 > cm1 <- lm (y ~ x1*x2 + x3 + x4 + x5, data)
56 > ## add class lm to rm1 (for now)
57 > class(rm1) <- c(class(rm1), "lm")
58 > class(rm0) <- c(class(rm0), "lm")
142 > #drop1(rm1) ## drop.lm does not return valid results (yet)!
175 > #dfbeta(rm1)
181 + all.equal(hv1, stats:::hatvalues.lm(rm1), tol=1e-15),
[all …]
H A Dweights.Rout.save31 > data$x5 <- data$x3 + data$x4 ## lm() will have 'x5' "aliased" (and give coef = NA)
44 > ## fit a classic model --> easier to compare to lm()
50 > (cm0 <- lm (y ~ x1*x2 + x3 + x4 + x5 + offset(os), data))
53 lm(formula = y ~ x1 * x2 + x3 + x4 + x5 + offset(os), data = data)
63 > (cm1 <- lm (y ~ x1*x2 + x3 + x4 + x5 + offset(os), data, weights=weights))
66 lm(formula = y ~ x1 * x2 + x3 + x4 + x5 + offset(os), data = data,
77 > (cm2 <- lm (y ~ x1*x2 + x3 + x4 + x5, data2, offset=os))
80 lm(formula = y ~ x1 * x2 + x3 + x4 + x5, data = data2, offset = os)
301 > ## test class "lm" methods that do not depend on weights
312 > ## class "lm" methods that depend on weights
[all …]
/dports/x11-toolkits/scintilla/scite/src/
H A Dr.properties19 …dfbeta dfbetas dffits dgamma dgeom dget dhyper diag diff diffinv difftime digamma dim dimnames dir…
/dports/editors/scite/scite/src/
H A Dr.properties19 …dfbeta dfbetas dffits dgamma dgeom dget dhyper diag diff diffinv difftime digamma dim dimnames dir…
/dports/math/R-cran-VGAM/VGAM/
H A DNAMESPACE248 "integrate", "is.empty.model", "lm.fit", "median",
394 importFrom("stats", dfbeta) # Added 20140509
395 export(dfbeta, dfbetavlm)
396 exportMethods(dfbeta)
H A DNEWS53 o Deprecated: dgenpois(), genpoisson(), [dpqr]gaitnbinom.m[ix,lm]().
54 gatnbinomial.m[ix,lm](dpqr), [dpqr]gaitbinom.mlm(),
867 o dfbeta() returns the difference between the coeffs.
992 Also, depvar(type = c("lm", "lm2")) has a 'type' argument.
1082 @extra$ncols_X_lm becomes @extra$ncols.X.lm.
1155 o fnormal1()@initialize was faulty wrt lm.wfit().
1243 o constraints.vlm(type = c("vlm", "lm")) has been changed to
1244 constraints.vlm(type = c("lm", "term")) [respectively].
1650 also including base's lm(), glm(), etc.
1815 lm, glm, predict.lm, predict.mlm, predict.glm.
[all …]
/dports/math/R/R-4.1.2/tests/Examples/
H A Dstats-Ex.Rout.save8411 > ### rstandard.lm rstandard.glm rstudent rstudent.lm rstudent.glm dfbeta
8412 > ### dfbeta.lm dfbetas dfbetas.lm dffits covratio cooks.distance
9204 > lm.D9 <- lm(weight ~ group)
9266 > utils::str(lmI <- lm.influence(lm.SR))
9291 > ### Aliases: family.lm formula.lm residuals.lm labels.lm
9320 > ### Aliases: lm.fit lm.wfit .lm.fit
9353 > str(lm. <- lm.fit (x = X, y = y))
9374 > lm.. <- .lm.fit(X,y)
9375 > lm.w <- .lm.fit(X*sqrt(w), y*sqrt(w))
18268 > lm.D9 <- lm(weight ~ group)
[all …]
/dports/math/libRmath/R-4.1.1/tests/Examples/
H A Dstats-Ex.Rout.save8411 > ### rstandard.lm rstandard.glm rstudent rstudent.lm rstudent.glm dfbeta
8412 > ### dfbeta.lm dfbetas dfbetas.lm dffits covratio cooks.distance
9204 > lm.D9 <- lm(weight ~ group)
9266 > utils::str(lmI <- lm.influence(lm.SR))
9291 > ### Aliases: family.lm formula.lm residuals.lm labels.lm
9320 > ### Aliases: lm.fit lm.wfit .lm.fit
9353 > str(lm. <- lm.fit (x = X, y = y))
9374 > lm.. <- .lm.fit(X,y)
9375 > lm.w <- .lm.fit(X*sqrt(w), y*sqrt(w))
18264 > lm.D9 <- lm(weight ~ group)
[all …]
/dports/math/R/R-4.1.2/doc/
H A DNEWS.1750 o glm.fit.null(), lm.fit.null() and lm.wfit.null() are defunct.
758 o Unnecessary methods coef.{g}lm and fitted.{g}lm have been
1811 o glm.fit.null(), lm.fit.null() and lm.wfit.null() are deprecated.
1917 model) lm() and glm() fits.
2210 o lm.(w)fit failed if the fit had rank 0.
2450 o New generic functions influence(), hatvalues() and dfbeta()
4909 "lm" and "glm".
5488 o lm.influence(), plot.lm(), influence.measures() and the
6562 calling anovalist.lm() directly.
6953 o lm.fit & lm.wfit (and hence lm) now give understandable error
[all …]
/dports/math/libRmath/R-4.1.1/doc/
H A DNEWS.1750 o glm.fit.null(), lm.fit.null() and lm.wfit.null() are defunct.
758 o Unnecessary methods coef.{g}lm and fitted.{g}lm have been
1811 o glm.fit.null(), lm.fit.null() and lm.wfit.null() are deprecated.
1917 model) lm() and glm() fits.
2210 o lm.(w)fit failed if the fit had rank 0.
2450 o New generic functions influence(), hatvalues() and dfbeta()
4909 "lm" and "glm".
5488 o lm.influence(), plot.lm(), influence.measures() and the
6562 calling anovalist.lm() directly.
6953 o lm.fit & lm.wfit (and hence lm) now give understandable error
[all …]

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