integrate               package:stats               R Documentation

_I_n_t_e_g_r_a_t_i_o_n _o_f _O_n_e-_D_i_m_e_n_s_i_o_n_a_l _F_u_n_c_t_i_o_n_s

_D_e_s_c_r_i_p_t_i_o_n:

     Adaptive quadrature of functions of one variable over a finite or
     infinite interval.

_U_s_a_g_e:

     integrate(f, lower, upper, subdivisions=100,
               rel.tol = .Machine$double.eps^0.25, abs.tol = rel.tol,
               stop.on.error = TRUE, keep.xy = FALSE, aux = NULL, ...)

_A_r_g_u_m_e_n_t_s:

       f: an R function taking a numeric first argument and returning a
          numeric vector of the same length.  Returning a non-finite
          element will generate an error.

lower, upper: the limits of integration.  Can be infinite.

subdivisions: the maximum number of subintervals.

 rel.tol: relative accuracy requested.

 abs.tol: absolute accuracy requested.

stop.on.error: logical. If true (the default) an error stops the
          function.  If false some errors will give a result with a
          warning in the 'message' component.

 keep.xy: unused.  For compatibility with S.

     aux: unused.  For compatibility with S.

     ...: additional arguments to be passed to 'f'.  Remember to use
          argument names _not_ matching those of 'integrate(.)'!

_D_e_t_a_i_l_s:

     If one or both limits are infinite, the infinite range is mapped
     onto a finite interval.

     For a finite interval, globally adaptive interval subdivision is
     used in connection with extrapolation by the Epsilon algorithm.

     'rel.tol' cannot be less than 'max(50*.Machine$double.eps,
     0.5e-28)' if 'abs.tol <= 0'.

_V_a_l_u_e:

     A list of class '"integrate"' with components 

   value: the final estimate of the integral.

abs.error: estimate of the modulus of the absolute error.

subdivisions: the number of subintervals produced in the subdivision
          process.

 message: '"OK"' or a character string giving the error message.

    call: the matched call.

_N_o_t_e:

     Like all numerical integration routines, these evaluate the
     function on a finite set of points.  If the function is
     approximately constant (in particular, zero) over nearly all its
     range it is possible that the result and error estimate may be
     seriously wrong.

     When integrating over infinite intervals do so explicitly, rather
     than just using a large number as the endpoint.  This increases
     the chance of a correct answer - any function whose integral over
     an infinite interval is finite must be near zero for most of that
     interval.

_R_e_f_e_r_e_n_c_e_s:

     Based on QUADPACK routines 'dqags' and 'dqagi' by R. Piessens and
     E. deDoncker-Kapenga, available from Netlib.

     See
      R. Piessens, E. deDoncker-Kapenga, C. Uberhuber, D. Kahaner
     (1983) _Quadpack: a Subroutine Package for Automatic Integration_;
     Springer Verlag.

_S_e_e _A_l_s_o:

     The function 'adapt' in the 'adapt' package on CRAN, for
     multivariate integration.

_E_x_a_m_p_l_e_s:

     integrate(dnorm, -1.96, 1.96)
     integrate(dnorm, -Inf, Inf)

     ## a slowly-convergent integral
     integrand <- function(x) {1/((x+1)*sqrt(x))}
     integrate(integrand, lower = 0, upper = Inf)

     ## don't do this if you really want the integral from 0 to Inf
     integrate(integrand, lower = 0, upper = 10)
     integrate(integrand, lower = 0, upper = 100000)
     integrate(integrand, lower = 0, upper = 1000000, stop.on.error = FALSE)

     try(integrate(function(x) 2, 0, 1))  ## no vectorizable function
     integrate(function(x) rep(2, length(x)), 0, 1)  ## correct

     ## integrate can fail if misused
     integrate(dnorm,0,2)
     integrate(dnorm,0,20)
     integrate(dnorm,0,200)
     integrate(dnorm,0,2000)
     integrate(dnorm,0,20000) ## fails on many systems
     integrate(dnorm,0,Inf)   ## works

