# Why does expressing one function...
require(ctest) t.test
# return only
function (x, ...) UseMethod("t.test") <environment: namespace:ctest>
# but expressing another function
shapiro.test
# returns more complete code?
function (x) { DNAME <- deparse(substitute(x)) x <- sort(x[complete.cases(x)]) n <- length(x) if (n < 3 || n > 5000) stop("sample size must be between 3 and 5000")
Short answer: Unless you're programming your own functions, you don't need to worry about that.
Long answer: Because the first is generic - it looks at what kind of data you're testing (two vectors, a formula, whatever, ...) and calls the appropriate sub-function. shapiro.test does not; it just takes one data format, and stops in its tracks if that's not what you've provided.
The ideas behind this are documented in "Writing R Extensions" (R-exts.pdf) which is supplied with binary R distributions, and is available from CRAN. See chapter 6, "Generic functions and methods", in the version that accompanies R-1.8.1.
Cheers
Jason -- Indigo Industrial Controls Ltd. http://www.indigoindustrial.co.nz 64-21-343-545 [EMAIL PROTECTED]
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