kurtosis        package:PerformanceAnalytics        R Documentation

_K_u_r_t_o_s_i_s

_D_e_s_c_r_i_p_t_i_o_n:

     compute kurtosis of a univariate distribution

_U_s_a_g_e:

     kurtosis(x, na.rm = FALSE, method = c("excess", "moment", "fisher"), ...)

_A_r_g_u_m_e_n_t_s:

   na.rm: a logical. Should missing values be removed? 

  method: a character string which specifies the method of computation.
          These are either '"moment"', '"fisher"', or '"excess"'. If
          '"excess"' is selected, then the value of the kurtosis is
          computed by the '"moment"' method and a value of 3 will be
          subtracted. The '"moment"' method is based on the definitions
          of kurtosis for distributions; these forms should be used
          when resampling (bootstrap or jackknife). The '"fisher"'
          method correspond to the usual "unbiased" definition of
          sample variance, although in the case of kurtosis exact
          unbiasedness is not possible. 

       x: a numeric vector or object. 

     ...: arguments to be passed. 

_D_e_t_a_i_l_s:

     This function was ported from the RMetrics package fUtilities to
     eliminate a dependency on fUtilties being loaded every time.  This
     function is identical except for the addition of 'checkData' and
     additional labeling.

_V_a_l_u_e:

     'kurtosis' returns the value of the statistics, a numeric value.
     An attribute which reports the used method is added.

_A_u_t_h_o_r(_s):

     Diethelm Wuertz

_S_e_e _A_l_s_o:

     'skewness'.

_E_x_a_m_p_l_e_s:

     ## mean -
     ## var -
        # Mean, Variance:
        r = rnorm(100)
        mean(r)
        var(r)

     ## kurtosis -
        kurtosis(r)

     data(managers)
     kurtosis(managers[,1:8])