simmixstock1            package:mixstock            R Documentation

_S_i_m_u_l_a_t_e _m_a_r_k_e_r _f_r_e_q_u_e_n_c_i_e_s _a_n_d _d_i_s_t_r_i_b_u_t_i_o_n_s _i_n _a _m_i_x_e_d _s_t_o_c_k

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

     Functions for simulating marker frequency distributions and
     samples in source and mixed populations

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

     simmixstock1(sampsize = NULL, true.freq = matrix(c(0.65, 0.33, 0.01, 
         0.01, 0.33, 0.65, 0.01, 0.01), ncol = 2), true.contrib = c(0.9, 
         0.1), boot = FALSE, param = FALSE, data = NULL, rseed = 1004, 
         nboot = 1000, chainlen = NULL, ests = c("cmlboot.nonpar", 
             "cmlboot.par", "umlboot.nonpar", "umlboot.par", "mcmc"), 
         verbose = FALSE, contrib.only = FALSE)
     sim.mark.freq(H,R,g.mark,g.source)

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

sampsize: total sampsize: half from mixed population, (1/(2R)) from
          each source

true.freq: matrix of marker frequencies in sources

true.contrib: contributions from each source to source population

    boot: bootstrap existing data?

   param: parametric bootstrap?

    data: original data set to bootstrap

   nboot: number of bootstrap samples

chainlen: chain length for MCMC

    ests: list of estimates to produce (parametric or nonparametric
          bootstrap for CML or UML estimation, MCMC)

       H: number of markers

       R: number of sources

  g.mark: geometric distribution parameter for marker frequency

g.source: geometric distribution parameter for source contribution

   rseed: random number seed

contrib.only: save only source contributions in MCMC chain results?

 verbose: verbose output?

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

     'sim.mark.freq' just returns an HxR matrix of  marker
     'simmixstock1' returns a list with a 'genboot' result for each
     type of estimate requested;

_A_u_t_h_o_r(_s):

     Ben Bolker

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

     'genboot', 'mysumvec'

