

pbirth(event)                                R Documentation

_F_i_t _O_v_e_r_d_i_s_p_e_r_s_e_d _C_o_u_n_t _D_a_t_a _a_s _a _B_i_r_t_h _P_r_o_c_e_s_s

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

     `pbirth' fits binomial, binomial exponential, binomial
     logistic, binomial total, Poisson, Poisson exponential,
     negative binomial, gen(eralized) negative binomial, and
     generalized negative binomial processes as a birth pro-
     cess.

_U_s_a_g_e_:

     pbirth(frequencies, p, intensity="negative binomial",
             type="spectral decomposition", print.level=0, typsiz=abs(p),
             ndigit=10, gradtol=0.00001, stepmax=10*sqrt(p%*%p),
             steptol=0.00001, iterlim=100, fscale=1)

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

frequencies: Vector of frequencies or a matrix with each row
          a different series of frequencies.

       p: Vector of initial estimates.

intensity: The intensity function of the process: binomial,
          binomial exdponential, binomial logistic, binomial
          total, Poisson, Poisson exponential, negative
          binomial, or gen(eralized) negative binomial.

    type: Algorithm used for matrix exponentiation: spectral
          decomposition or series approximation.

  others: Arguments controlling `nlm'.

_A_u_t_h_o_r_(_s_)_:

     J.K. Lindsey

_R_e_f_e_r_e_n_c_e_s_:

     Faddy, M.J. and Fenlon, J.S. (1999) Stochastic mod-
     elling of the invasion process of nematodes in fly lar-
     vae. Applied Statistics 48: 31-37.

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

     y <- rnbinom(100,2,0.6)
     fr <- tabulate(y)
     pbirth(fr, p=log(-log(0.7)), intensity="Poisson", type="series")
     pbirth(fr, p=c(log(-log(0.7)),log(5)),
             intensity="negative binomial", type="series")
     pbirth(fr, p=c(log(-log(0.7)),log(5),-1),
             intensity="gen negative binomial", type="series")

