Which of the following items is required for an R package to pass R CMD check without any warnings or errors?
Answer:
Which of the following is a generic function in a fresh installation of R, with only the default packages loaded? (Select all that apply)
Answer:
show## standardGeneric for "show" defined from package "methods"
##
## function (object)
## standardGeneric("show")
## <bytecode: 0x000000000859e978>
## <environment: 0x0000000007ad3dd8>
## Methods may be defined for arguments: object
## Use showMethods("show") for currently available ones.
## (This generic function excludes non-simple inheritance; see ?setIs)mean## function (x, ...)
## UseMethod("mean")
## <bytecode: 0x000000000829ba68>
## <environment: namespace:base>predict## function (object, ...)
## UseMethod("predict")
## <bytecode: 0x000000000711af78>
## <environment: namespace:stats>dgamma## function (x, shape, rate = 1, scale = 1/rate, log = FALSE)
## {
## if (!missing(rate) && !missing(scale)) {
## if (abs(rate * scale - 1) < 1e-15)
## warning("specify 'rate' or 'scale' but not both")
## else stop("specify 'rate' or 'scale' but not both")
## }
## .Call(C_dgamma, x, shape, scale, log)
## }
## <bytecode: 0x0000000009383ee8>
## <environment: namespace:stats>colSums## function (x, na.rm = FALSE, dims = 1L)
## {
## if (is.data.frame(x))
## x <- as.matrix(x)
## if (!is.array(x) || length(dn <- dim(x)) < 2L)
## stop("'x' must be an array of at least two dimensions")
## if (dims < 1L || dims > length(dn) - 1L)
## stop("invalid 'dims'")
## n <- prod(dn[id <- seq_len(dims)])
## dn <- dn[-id]
## z <- if (is.complex(x))
## .Internal(colSums(Re(x), n, prod(dn), na.rm)) + (0+1i) *
## .Internal(colSums(Im(x), n, prod(dn), na.rm))
## else .Internal(colSums(x, n, prod(dn), na.rm))
## if (length(dn) > 1L) {
## dim(z) <- dn
## dimnames(z) <- dimnames(x)[-id]
## }
## else names(z) <- dimnames(x)[[dims + 1L]]
## z
## }
## <bytecode: 0x00000000095c3238>
## <environment: namespace:base>lm## 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$drop.unused.levels <- TRUE
## mf[[1L]] <- quote(stats::model.frame)
## mf <- eval(mf, parent.frame())
## if (method == "model.frame")
## return(mf)
## else if (method != "qr")
## warning(gettextf("method = '%s' is not supported. Using 'qr'",
## method), domain = NA)
## mt <- attr(mf, "terms")
## y <- model.response(mf, "numeric")
## w <- as.vector(model.weights(mf))
## if (!is.null(w) && !is.numeric(w))
## stop("'weights' must be a numeric vector")
## offset <- as.vector(model.offset(mf))
## if (!is.null(offset)) {
## if (length(offset) != NROW(y))
## stop(gettextf("number of offsets is %d, should equal %d (number of observations)",
## length(offset), NROW(y)), domain = NA)
## }
## if (is.empty.model(mt)) {
## x <- NULL
## z <- list(coefficients = if (is.matrix(y)) matrix(, 0,
## 3) else numeric(), residuals = y, fitted.values = 0 *
## y, weights = w, rank = 0L, df.residual = if (!is.null(w)) sum(w !=
## 0) else if (is.matrix(y)) nrow(y) else length(y))
## if (!is.null(offset)) {
## z$fitted.values <- offset
## z$residuals <- y - offset
## }
## }
## else {
## x <- model.matrix(mt, mf, contrasts)
## z <- if (is.null(w))
## lm.fit(x, y, offset = offset, singular.ok = singular.ok,
## ...)
## else lm.wfit(x, y, w, offset = offset, singular.ok = singular.ok,
## ...)
## }
## class(z) <- c(if (is.matrix(y)) "mlm", "lm")
## z$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
## }
## <bytecode: 0x000000000983c410>
## <environment: namespace:stats>Answer:
What function is used to obtain the function body for an S4 method function?
Answer:
lease download the R package DDPQuiz3 from the course web site. Examine the createmean function implemented in the R/ sub-directory. What is the appropriate text to place above the createmean function for Roxygen2 to create a complete help file?
#' This function calculates the mean
#'
#' @param x is a numeric vector
#' @return the mean of x
#' @export
#' @examples
#' x <- 1:10
#' createmean(x)