brown.fit                package:ouch                R Documentation

_B_r_o_w_n_i_a_n-_m_o_t_i_o_n _m_o_d_e_l _o_f _e_v_o_l_u_t_i_o_n _a_l_o_n_g _a _p_h_y_l_o_g_e_n_e_t_i_c _t_r_e_e

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

     These functions relate to the Brownian motion model for
     phylogenetic evolution.

_b_r_o_w_n fits the parameters sigma and theta of this model to given data.

_b_r_o_w_n._d_e_v generates simulated data sets.

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

     brown.fit(data, node, ancestor, times)
     brown.dev(n = 1, node, ancestor, times, sigma, theta)

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

    data: Phenotypic data for extant species, i.e., at the terminal
          ends of the phylogenetic tree.

    node: Specification of the names of the nodes.

ancestor: Specification of the topology of the phylogenetic tree.  This
          is in the form of a character vector of node names, one for
          each node in the tree.  The i-th name is that of the ancestor
          of the i-th node.  The root node is distinguished by having
          no ancestor (i.e., NA).

   times: A vector of nonnegative numbers, one per node in the tree,
          specifying the time at which each node is located.  The root
          node should be assigned time 0.

       n: the number of simulated data sets to generate.

   sigma: the value of sigma to be used in the simulations.

   theta: the value of theta to be used in the simulations.

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

     brown returns a list of the following elements: 

   sigma: Maximum likelihood estimate of sigma.

   theta: Maximum likelihood estimate of theta.

       u: -2 log likelihood.

     aic: Akaike information criterion.

     sic: Schwartz information criterion (=BIC)

      df: Number of parameters estimated (= 2).


     brown.dev returns a data frame containing simulated data sets. 
     Each realization is a row.

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

     Aaron A. King <king at tiem dot utk dot edu>

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

     Butler, M.A. and A.A. King (2004) Phylogenetic comparative
     analysis: a modeling approach for adaptive evolution. American
     Naturalist, in press.

