Home / R Documentation / base / summary : Object Summaries summary: Object Summaries summary R Documentation Object Summaries Description summary is a generic

Home / R Documentation / base / summary : Object Summaries summary: Object Summaries summary R Documentation Object Summaries Description summary is a generic

of Variance Model summary.glm : Summarizing Generalized Linear Model Fits summary.lm : Summarizing Linear Model Fits summary.manova : Summary Method for

of Variance Model summary.glm : Summarizing Generalized Linear Model Fits summary.lm : Summarizing Linear Model Fits summary.manova : Summary Method for

in summary block, Default: NULL tooltip character, text for tooltip on the summary, Default: 'Click to

of Variance Model summary.glm : Summarizing Generalized Linear Model Fits summary.lm : Summarizing Linear Model Fits summary.manova : Summary Method for

of Variance Model summary.glm : Summarizing Generalized Linear Model Fits summary.lm : Summarizing Linear Model Fits summary.manova : Summary Method for

of Variance Model summary.glm : Summarizing Generalized Linear Model Fits summary.lm : Summarizing Linear Model Fits summary.manova : Summary Method for

of Variance Model summary.glm : Summarizing Generalized Linear Model Fits summary.lm : Summarizing Linear Model Fits summary.manova : Summary Method for

of Variance Model summary.glm : Summarizing Generalized Linear Model Fits summary.lm : Summarizing Linear Model Fits summary.manova : Summary Method for

of Variance Model summary.glm : Summarizing Generalized Linear Model Fits summary.lm : Summarizing Linear Model Fits summary.manova : Summary Method for

of Variance Model summary.glm : Summarizing Generalized Linear Model Fits summary.lm : Summarizing Linear Model Fits summary.manova : Summary Method for

of Variance Model summary.glm : Summarizing Generalized Linear Model Fits summary.lm : Summarizing Linear Model Fits summary.manova : Summary Method for

of Variance Model summary.glm : Summarizing Generalized Linear Model Fits summary.lm : Summarizing Linear Model Fits summary.manova : Summary Method for

of Variance Model summary.glm : Summarizing Generalized Linear Model Fits summary.lm : Summarizing Linear Model Fits summary.manova : Summary Method for

of Variance Model summary.glm : Summarizing Generalized Linear Model Fits summary.lm : Summarizing Linear Model Fits summary.manova : Summary Method for

of Variance Model summary.glm : Summarizing Generalized Linear Model Fits summary.lm : Summarizing Linear Model Fits summary.manova : Summary Method for

of Variance Model summary.glm : Summarizing Generalized Linear Model Fits summary.lm : Summarizing Linear Model Fits summary.manova : Summary Method for

of Variance Model summary.glm : Summarizing Generalized Linear Model Fits summary.lm : Summarizing Linear Model Fits summary.manova : Summary Method for

of Variance Model summary.glm : Summarizing Generalized Linear Model Fits summary.lm : Summarizing Linear Model Fits summary.manova : Summary Method for

of Variance Model summary.glm : Summarizing Generalized Linear Model Fits summary.lm : Summarizing Linear Model Fits summary.manova : Summary Method for

of Variance Model summary.glm : Summarizing Generalized Linear Model Fits summary.lm : Summarizing Linear Model Fits summary.manova : Summary Method for

of Variance Model summary.glm : Summarizing Generalized Linear Model Fits summary.lm : Summarizing Linear Model Fits summary.manova : Summary Method for

of Variance Model summary.glm : Summarizing Generalized Linear Model Fits summary.lm : Summarizing Linear Model Fits summary.manova : Summary Method for

of Variance Model summary.glm : Summarizing Generalized Linear Model Fits summary.lm : Summarizing Linear Model Fits summary.manova : Summary Method for

of Variance Model summary.glm : Summarizing Generalized Linear Model Fits summary.lm : Summarizing Linear Model Fits summary.manova : Summary Method for

of Variance Model summary.glm : Summarizing Generalized Linear Model Fits summary.lm : Summarizing Linear Model Fits summary.manova : Summary Method for

of Variance Model summary.glm : Summarizing Generalized Linear Model Fits summary.lm : Summarizing Linear Model Fits summary.manova : Summary Method for

of Variance Model summary.glm : Summarizing Generalized Linear Model Fits summary.lm : Summarizing Linear Model Fits summary.manova : Summary Method for

of Variance Model summary.glm : Summarizing Generalized Linear Model Fits summary.lm : Summarizing Linear Model Fits summary.manova : Summary Method for

ways of summarising by variables that should not be # included in the summary daply(baseball[, c(2

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

of Variance Model summary.glm : Summarizing Generalized Linear Model Fits summary.lm : Summarizing Linear Model Fits summary.manova : Summary Method for

of Variance Model summary.glm : Summarizing Generalized Linear Model Fits summary.lm : Summarizing Linear Model Fits summary.manova : Summary Method for

of Variance Model summary.glm : Summarizing Generalized Linear Model Fits summary.lm : Summarizing Linear Model Fits summary.manova : Summary Method for

of Variance Model summary.glm : Summarizing Generalized Linear Model Fits summary.lm : Summarizing Linear Model Fits summary.manova : Summary Method for

1,0,0,0), x=c(1,0,0,1,0,1,1,1,0,0)) summary(coxph(Surv(start, stop

warning in a pleasing form. Usage warnings(...) ## S3 method for class 'warnings' summary(object, ...) ## S3 method for

generic function: methods can be defined for it directly or via the Summary group generic. For

generic functions: methods can be defined for them individually or via the Summary group generic. For

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

generic function: methods can be defined for it directly or via the Summary group generic. For

generic function: methods can be defined for it directly or via the Summary group generic. For

showErrorCalls : a logical. Should warning and error messages show a summary of the

inherit from the class (if any) returned by that function. The function summary (i.e., summary.glm ) can

Language . Wadsworth & Brooks/Cole. See Also library , detach , search , objects , environment , with . Examples require(utils) summary(women$height) # refers to

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary

generic functions: methods can be defined for them individually or via the Summary group generic. For

an R object, a diagnostic function and an alternative to summary (and to

generic function: methods can be defined for it directly or via the Summary group generic. For

generic function: methods can be defined for it directly or via the Summary group generic. For

generic function: methods can be defined for it directly or via the Summary group generic. For

of Variance Model summary.glm : Summarizing Generalized Linear Model Fits summary.lm : Summarizing Linear Model Fits summary.manova : Summary Method for

generic function: methods can be defined for it directly or via the Summary group generic. For

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

Details A MD5 ‘hash’ or ‘checksum’ or ‘message digest’ is a 128-bit summary of the

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary

an R object, a diagnostic function and an alternative to summary (and to

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

will handle classed objects with methods for the Math , Ops and Summary group generics. seq.int

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

25,21,19,18), lot2 = c(69,35,26,21,18,16,13,12,12)), list(summary(glm(lot1 ~ log(u

applies a function block-wise. Examples require(stats) by(warpbreaks[, 1:2], warpbreaks[,"tension"], summary) by(warpbreaks[, 1], warpbreaks

25,21,19,18), lot2 = c(69,35,26,21,18,16,13,12,12)), list(summary(glm(lot1 ~ log(u

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

function unit.c is provided for combining unit objects. Certain arithmetic and summary operations are defined for

the first plant fm1 <- nls(uptake ~ SSasymp(conc, Asym, lrc, c0), data = CO2, subset = Plant == "Qn1") summary(fm1) ## fit each plant

will handle classed objects with methods for the Math , Ops and Summary group generics. seq.int

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

and for the min , max , and range generics in Summary of "ordered

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

par(mfrow = 2:1, mgp = c(3,1,0)/2, mar = .1+c(3,3:1)) summary(d.Titanic <- as.data

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular

substr : Substrings of a Character Vector sum : Sum of Vector Elements summary : Object Summaries svd : Singular