运行 do.call() 函数而不打印其所有参数

如何解决运行 do.call() 函数而不打印其所有参数

当我运行 do.call() 时，它会打印很多我不希望它打印的东西。默认情况下，它会打印函数的源代码以及我提供的完整参数。例如：

y = rnorm(100)
x = rnorm(100)
dat = data.frame(y,x)
do.call(lm,list(formula=as.formula('y~x'),data=dat))

最后一行执行 lm() 调用，正如我希望的那样，但它也会打印出来：

Call:
(function (formula,data,subset,weights,na.action,method = "qr",model = TRUE,x = FALSE,y = FALSE,qr = TRUE,singular.ok = TRUE,contrasts = NULL,offset,...) 
{
    ret.x <- x
    ret.y <- y
    cl <- match.call()
    mf <- match.call(expand.dots = FALSE)
    m <- match(c("formula","data","subset","weights","na.action","offset"),names(mf),0L)
    mf <- mf[c(1L,m)]
    mf$drop.unused.levels <- TRUE
    mf[[1L]] <- quote(stats::model.frame)
    mf <- eval(mf,parent.frame())
    if (method == "model.frame") 
        return(mf)
    else if (method != "qr") 
        warning(gettextf("method = '%s' is not supported. Using 'qr'",method),domain = NA)
    mt <- attr(mf,"terms")
    y <- model.response(mf,"numeric")
    w <- as.vector(model.weights(mf))
    if (!is.null(w) && !is.numeric(w)) 
        stop("'weights' must be a numeric vector")
    offset <- model.offset(mf)
    mlm <- is.matrix(y)
    ny <- if (mlm) 
        nrow(y)
    else length(y)
    if (!is.null(offset)) {
        if (!mlm) 
            offset <- as.vector(offset)
        if (NROW(offset) != ny) 
            stop(gettextf("number of offsets is %d,should equal %d (number of observations)",NROW(offset),ny),domain = NA)
    }
    if (is.empty.model(mt)) {
        x <- NULL
        z <- list(coefficients = if (mlm) matrix(NA_real_,ncol(y)) else numeric(),residuals = y,fitted.values = 0 * 
            y,weights = w,rank = 0L,df.residual = if (!is.null(w)) sum(w != 
            0) else ny)
        if (!is.null(offset)) {
            z$fitted.values <- offset
            z$residuals <- y - offset
        }
    }
    else {
        x <- model.matrix(mt,mf,contrasts)
        z <- if (is.null(w)) 
            lm.fit(x,y,offset = offset,singular.ok = singular.ok,...)
        else lm.wfit(x,w,...)
    }
    class(z) <- c(if (mlm) "mlm","lm")
    z$na.action <- attr(mf,"na.action")
    z$offset <- offset
    z$contrasts <- attr(x,"contrasts")
    z$xlevels <- .getXlevels(mt,mf)
    z$call <- cl
    z$terms <- mt
    if (model) 
        z$model <- mf
    if (ret.x) 
        z$x <- x
    if (ret.y) 
        z$y <- y
    if (!qr) 
        z$qr <- NULL
    z
})(formula = y ~ x,data = structure(list(y = c(0.645552938260277,-1.03674741955656,-1.36678177623718,0.518879099012354,-0.914092586089106,1.85633406839752,2.33525903047248,1.14722981159834,0.275299886900546,-0.911857314399479,0.906716193555437,-1.84262025693996,-0.721153566116692,2.48197346041889,0.91637339376205,-0.0482959098521057,-0.412766187814658,0.565508110918711,0.798593902512974,1.02370248417386,1.43489462095486,-0.00595661011583523,0.750101041920158,0.0298980087576892,0.578596357299012,2.06230646195833,0.837325836562161,-0.033216036814055,-0.584230631296736,-1.1266387975112,-0.689512161483645,0.291619808691663,-1.69357030189337,0.978250304761813,-0.755591443050875,0.0581812013160168,0.160793605900764,0.54544692679131,2.67118590214976,0.0423406641418217,0.441445795983119,-1.58961605562098,-0.22489452744228,-0.333387697959592,-0.606119646136784,-1.11971038685321,-0.515251196689386,0.388206565971871,-1.19191379429206,-1.17626555070404,0.549984711717793,0.189356928489049,-0.732133641764621,0.428942994232102,-1.10713109993258,-1.64799963728532,1.52406805730385,-0.817775798184812,-0.228579583992437,0.222167620842928,-0.449100415184847,-1.37899113402036,-1.22746769483453,1.69732446155693,0.910274215721166,-0.266266303066525,0.000833984550746797,-0.693636029432195,1.05678031077105,0.765504099803622,-0.62851012512813,-1.02162531958929,-0.342983933183841,-0.614040542906127,-0.144903744412403,-1.86846800255061,-0.471608270196133,0.132626367278681,1.74544503775265,-0.471487649922146,0.604438400086659,0.825455235134079,0.155961973523576,0.207420563250091,-0.130175758501042,0.629838988210575,-0.787614987225754,-0.483446505017937,-0.248709520763105,0.950993202262253,0.825213623331804,-0.500480946731697,-1.37680920242343,0.181153862811113,0.408046651578768,0.341494326390166,1.06940090717878,-1.22351447343963,-0.539163919598057,-0.766566843828881),x = c(0.59188040130602,0.1051430615256,0.209172959698725,-0.191070094060143,-0.953114116953908,-1.33637617471067,-0.769931523816078,1.19685219431872,2.00578388289767,0.0970818701412437,1.14507289348526,-0.667384225193717,-0.710354102271159,-0.326733273119207,1.50747585292862,0.510175505755495,0.432586204465598,0.605913508749864,-0.0797253150799987,-0.289868926776903,0.195719152585662,-1.08048882970833,-1.02806030503763,-0.955922907449149,-0.321714001459428,-0.0125625217985859,1.93972419212178,-1.2770087750596,-0.438044664481769,-0.16799844875219,0.737082811731615,-0.0217890205667605,-1.74348276484748,0.924385228062877,0.41847902246872,-0.153295341243861,1.50625650628283,-0.313786939328656,-0.72728516319703,0.130203275918779,-0.48742154233068,-0.0373985569171018,0.571708971495553,-0.149970891031242,0.0936771019912061,0.678489222500144,1.43310528753968,1.34167795827941,-9.67810025788311e-05,-2.81148656250494,-0.738982905660057,-2.01439275772803,0.122587160911615,-0.68236104257436,0.814172850108428,-0.679019473616009,0.9500158307568,-1.20692941419126,-0.245766342791828,-0.699289303631653,0.840933442954149,-1.10606335516112,-0.807003021163596,-0.448282105485891,0.514625936806471,-2.18234212156675,2.23461517185016,0.614164437989616,-2.16424418381578,2.10614632906954,-1.501290121483,0.133628764048144,-0.371497644963806,-1.09326848929288,-0.876160219188844,0.609731708125737,1.71889085217346,0.511989619195513,-1.69804077361953,-1.4931940305771,-1.41882351403557,1.43631793534341,-0.329057398411564,0.0188775594432232,1.00838379625486,-0.0685665648915033,0.57463373913359,0.153745024822862,1.50108777993883,1.35180164685218,1.30563013075212,-0.0934214107302569,1.21967023498808,2.71509985919089,-1.06079909507698,0.104930565833438,-0.640079250392443,-0.896427447908767,-0.281678332849185,-1.31186538595782)),class = "data.frame",row.names = c(NA,-100L)))

Coefficients:
(Intercept)            x  
    0.01252      0.07049  

有没有办法让它不打印所有这些东西？

解决方法

使用 "lm" 而不是 lm 和 quote(dat) 而不是 dat 。 as.formula('y~x') 也可以写成 y ~ x 虽然两者都给出相同的输出。

do.call("lm",list(y ~ x,data = quote(dat)))

给予：

Call:
lm(formula = y ~ x,data = dat)

Coefficients:
(Intercept)            x  
    0.03577      0.01136