operators-methods           package:distr           R Documentation

_M_e_t_h_o_d_s _f_o_r _o_p_e_r_a_t_o_r_s +,-,*,/ _i_n _P_a_c_k_a_g_e '_d_i_s_t_r'

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

     operator-methods

_M_e_t_h_o_d_s:


     - 'signature(e1 = "UnivariateDistribution")':

          application of `-' to this univariate distribution

     * 'signature(e1 = "UnivariateDistribution", e2 = "numeric")':

          multiplication of this univariate  distribution by an object
          of class `numeric'

     / 'signature(e1 = "UnivariateDistribution", e2 = "numeric")':

          division of this univariate distribution by an object of
          class `numeric'

     + 'signature(e1 = "UnivariateDistribution", e2 = "numeric")':

          addition of this univariate distribution to an object of
          class `numeric'

     - 'signature(e1 = "UnivariateDistribution", e2 = "numeric")':

          subtraction of an object of class `numeric' from this
          univariate distribution 

     * 'signature(e1 = "numeric", e2 = "UnivariateDistribution")':

          multiplication of this univariate distribution by an object
          of class `numeric'

     + 'signature(e1 = "numeric", e2 = "UnivariateDistribution")':

          addition of this univariate distribution to an object of
          class `numeric'

     - 'signature(e1 = "numeric", e2 = "UnivariateDistribution")':

          subtraction of this univariate distribution from an object of
          class `numeric'

     + 'signature(e1 = "UnivariateDistribution", e2 =
          "UnivariateDistribution")':

          Convolution of two univariate distributions. The slots p, d
          and q are approximated by grids.

     - 'signature(e1 = "UnivariateDistribution", e2 =
          "UnivariateDistribution")':

          Convolution of two univariate distributions. The slots p, d
          and q are approximated by grids.

     - 'signature(e1 = "AbscontDistribution")':

          application of `-' to this absolutely continuous distribution

     * 'signature(e1 = "AbscontDistribution", e2 = "numeric")':

          multiplication of this absolutely continuous  distribution by
          an object of class `numeric'

     / 'signature(e1 = "AbscontDistribution", e2 = "numeric")':

          division of this absolutely continuous  distribution by an
          object of class `numeric'

     + 'signature(e1 = "AbscontDistribution", e2 = "numeric")':

          addition of this absolutely continuous  distribution to an
          object of class `numeric'

     - 'signature(e1 = "AbscontDistribution", e2 = "numeric")':

          subtraction of an object of class `numeric' from this
          absolutely continuous distribution 

     * 'signature(e1 = "numeric", e2 = "AbscontDistribution")':

          multiplication of this absolutely continuous  distribution by
          an object of class `numeric'

     + 'signature(e1 = "numeric", e2 = "AbscontDistribution")':

          addition of this absolutely continuous  distribution to an
          object of class `numeric'

     - 'signature(e1 = "numeric", e2 = "AbscontDistribution")':

          subtraction of this absolutely continuous  distribution from
          an object of class `numeric'

     + 'signature(e1 = "AbscontDistribution", e2 =
          "AbscontDistribution")':

          Convolution of two absolutely continuous distributions. The
          slots p, d and q are approximated by grids.

     - 'signature(e1 = "AbscontDistribution", e2 =
          "AbscontDistribution")':

          Convolution of two absolutely continuous distributions. The
          slots p, d and q are approximated by grids.

     - 'signature(e1 = "DiscreteDistribution")':

          application of `-' to this discrete distribution

     * 'signature(e1 = "DiscreteDistribution", e2 = "numeric")':

          multiplication of this discrete distribution by an object of
          class `numeric'

     / 'signature(e1 = "DiscreteDistribution", e2 = "numeric")':

          division of this discrete distribution by an object of class
          `numeric'

     + 'signature(e1 = "DiscreteDistribution", e2 = "numeric")':

          addition of this discrete distribution to an object of class
          `numeric'

     - 'signature(e1 = "DiscreteDistribution", e2 = "numeric")':

          subtraction of an object of class `numeric' from this
          discrete distribution 

     * 'signature(e1 = "numeric", e2 = "DiscreteDistribution")':

          multiplication of this discrete distribution by an object of
          class `numeric'

     + 'signature(e1 = "numeric", e2 = "DiscreteDistribution")':

          addition of this discrete distribution to an object of class
          `numeric'

     - 'signature(e1 = "numeric", e2 = "DiscreteDistribution")':

          subtraction of this discrete distribution from an object of
          class `numeric'

     + 'signature(e1 = "DiscreteDistribution", e2 =
          "DiscreteDistribution")':

          Convolution of two discrete distributions. The slots p, d and
          q are approximated by grids.

     - 'signature(e1 = "DiscreteDistribution", e2 =
          "DiscreteDistribution")':

          Convolution of two discrete distributions. The slots p, d and
          q are approximated by grids.

     * 'signature(e1 = "numeric", e2 = "Norm")':

          multiplication of this normal distribution by an object of
          class `numeric'

     + 'signature(e1 = "numeric", e2 = "Norm")':

          addition of this normal distribution to an object of class
          `numeric'

     - 'signature(e1 = "numeric", e2 = "Norm")':

          subtraction of this normal distribution from an object of
          class `numeric'

     * 'signature(e1 = "Norm", e2 = "numeric")':

          multiplication of this normal distribution by an object of
          class `numeric'

     + 'signature(e1 = "Norm", e2 = "numeric")':

          addition of this normal distribution to an object of class
          `numeric'

     - 'signature(e1 = "Norm", e2 = "numeric")':

          subtraction of an object of class `numeric' from this normal
          distribution 

     / 'signature(e1 = "Norm", e2 = "numeric")':

          division of this normal distribution by an object of class
          `numeric'

     - 'signature(e1 = "Norm", e2 = "Norm")'

     + 'signature(e1 = "Norm", e2 = "Norm")': 

          For the normal distribution the exact convolution formulas
          are implemented thereby improving the general numerical
          approximation.

     * 'signature(e1 = "Unif", e2 = "numeric")':

          multiplication of this uniform distribution by an object of
          class `numeric'

     + 'signature(e1 = "Unif", e2 = "numeric")':

          addition of this uniform distribution to an object of class
          `numeric'

     + 'signature(e1 = "Binom", e2 = "Binom")':

          For two binomial distributions with the same probabilities
          the exact convolution formula is implemented thereby
          improving the general numerical approximation.

     + 'signature(e1 = "Pois", e2 = "Pois")':

          For the Poisson distribution the exact convolution formula is
          implemented thereby improving the general numerical
          approximation.

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

     'UnivariateDistribution-class' 'AbscontDistribution-class' 
      'DiscreteDistribution-class' 'Norm-class' 'Binom-class'
     'Pois-class'

