sample                 package:base                 R Documentation

_R_a_n_d_o_m _S_a_m_p_l_e_s _a_n_d _P_e_r_m_u_t_a_t_i_o_n_s

_D_e_s_c_r_i_p_t_i_o_n:

     `sample' takes a sample of the specified size from the elements of
     `x' using either with or without replacement.

_U_s_a_g_e:

     sample(x, size, replace = FALSE, prob = NULL)

_A_r_g_u_m_e_n_t_s:

       x: Either a (numeric, complex, character or logical) vector of
          more than one element from which to choose, or a positive
          integer.

    size: A positive integer giving the number of items to choose.

 replace: Should sampling be with replacement?

    prob: A vector of probability weights for obtaining the elements of
          the vector being sampled.

_D_e_t_a_i_l_s:

     If `x' has length 1, sampling takes place from `1:x'.

     By default `size' is equal to `length(x)' so that `sample(x)'
     generates a random permutation of the elements of `x' (or `1:x').

     The optional `prob' argument can be used to give a vector of
     weights for obtaining the elements of the vector being sampled.
     They need not sum to one, but they should be nonnegative and not
     all zero.  If `replace' is false, these probabilities are applied
     sequentially, that is the probability of choosing the next item is
     proportional to the probabilities amongst the remaining items. The
     number of nonzero weights must be at least `size' in this case.

_E_x_a_m_p_l_e_s:

     x <- 1:12
     # a random permutation
     sample(x)
     # bootstrap sampling
     sample(x,replace=TRUE)

     # 100 Bernoulli trials
     sample(c(0,1), 100, replace = TRUE)

