BiostatR Blog

 It is better to supply a initial point for robust regression ! x <- c(0.428571428571429, 0.2, 0.3, 0, 0, 0.2, 0, 0, 0.1, 0, 0.1,    0.1, 0, 0, 0, 0.3, 0.2, 0.3, 0.2, 0.2, 0, 0, 0, 0.2, 0.222222222222222,    0.1, 0, 0.4, 0.3, 0.5, 0, 0.4, 0.5, 0.8, 0.3, 0.1, 0.2, 0, 0.1,    0, 0.1, 0.1, 0.4, 0, 0, 0, 0, 0, 0, 0.333333333333333, 0.444444444444444,    0.2, 0.222222222222222, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,    0, 0, 0, 0, 0.4, 0, 0, 0, 0, 0.111111111111111, 0, 0, 0, 0, 0,    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,    0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,    0.5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0.2, 0, 0, 0, 0, 0, 0, 0) y <- c(0.369999388816617, 0.152260672623962, 0.392636473518975, 0.107742543910461,         0.105802942749025, 0.147888875829182, 0.0180958542177892, 0.00376865991773073,         0.00852273837059186, 0.00857162539273257, 0.112051915806605,         0.0755798935035902, 0.0268356635188166, 0.00419682981147497,         0

Often I want create a named vector and the names are stored in a variable. I must use a 2 steps function: names <- paste0("V", 1:100) A <- 1:100 names(A) <- names I search a way to do the same in a single step. Here is the solution: A <- structure(1:100, .Dim = 100L,                     .Dimnames = list(names)) But which one is the faster? names <- paste0("V", 1:100) library(microbenchmark) microbenchmark({     A <- 1:100     names(A) <- names},      {A <- structure(1:100, .Dim = 100L,                     .Dimnames = list(names))},      times = 1000L) Unit: microseconds                                                                 expr  min    lq     mean                             {     A <- 1:100     names(A) <- names } 1.02 1.068 1.222658  {     A <- structure(1:100, .Dim = 100L, .Dimnames = list(names)) } 5.78 6.295 6.486045  median     uq    max neval cld  1.2475 1.3310  4.658  1000  a   6.4090 6.5575 33.790  1000   b In conc