Extremes                package:base                R Documentation

_M_a_x_i_m_a _a_n_d _M_i_n_i_m_a

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

     Returns the (parallel) maxima and minima of the input values.

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

     max(..., na.rm=FALSE)
     min(..., na.rm=FALSE)

     pmax(..., na.rm=FALSE)
     pmin(..., na.rm=FALSE)

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

     ...: numeric arguments.

   na.rm: a logical indicating whether missing values should be
          removed.

_V_a_l_u_e:

     `max' and `min' return the maximum or minimum of all the values
     present in their arguments, as `integer' if all are `integer',  or
     as `double' otherwise.

     The minimum and maximum of an empty set are `+Inf' and `-Inf' (in
     this order!) which ensures transitivity, e.g., `min(x1, min(x2))
     == min(x1,x2)'. In R versions before 1.5, `min(integer(0)) ==
     .Machine$integer.max', and analogously for `max', preserving
     argument type, whereas from R version 1.5.0, `max(x) == -Inf' and
     `min(x) == +Inf' whenever `length(x) == 0' (after removing missing
     values if requested).

     If `na.rm' is `FALSE' an `NA' value in any of the arguments will
     cause a value of `NA' to be returned, otherwise `NA' values are
     ignored.

     `pmax' and `pmin' take several vectors as arguments and return a
     single vector giving the parallel maxima (or minima) of the
     vectors.  The first element of the result is the maximum (minimum)
     of the first elements of all the arguments, the second element of
     the result is the maximum (minimum) of the second elements of all
     the arguments and so on.  Shorter vectors are recycled if
     necessary.  If `na.rm' is `FALSE', `NA' values in the input
     vectors will produce `NA' values in the output.  If `na.rm' is
     `TRUE', `NA' values are ignored. `attributes' (such as `names' or
     `dim') are transferred from the first argument (if applicable).

_S_e_e _A_l_s_o:

     `range'.

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

     min(5:1,pi)
     pmin(5:1, pi)
     x <- sort(rnorm(100));  cH <- 1.35
     pmin(cH, quantile(x)) # no names
     pmin(quantile(x), cH) # has names
     plot(x, pmin(cH, pmax(-cH, x)), type='b', main= "Huber's function")

