autoini                 package:secr                 R Documentation

_I_n_i_t_i_a_l _P_a_r_a_m_e_t_e_r _V_a_l_u_e_s _f_o_r _S_E_C_R

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

     Find plausible initial parameter values for 'secr.fit'.  A
     simplified model is fitted by a fast ad hoc method.

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

     autoini(capthist, mask, detectfn = 0, thin = 0.2)

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

capthist: 'capthist' object

    mask: 'mask' object compatible with the detector layout in
          'capthist'

detectfn: shape of detection function 0 = half-normal

    thin: proportion of points to retain in mask 

_D_e_t_a_i_l_s:

     Plausible starting values are needed to avoid numerical problems
     when fitting SECR models. Actual models to be fitted will usually
     have more than the three basic parameters output by 'autoini';
     other initial values can usually be set to zero for 'secr.fit'. If
     the algorithm encounters problems obtaining a value for g0, the
     default value of 0.1 is returned. 

     Only the half-normal detection function is available in 'autoini'
     (cf other options in e.g. 'sim.capthist').

     'autoini' implements a modified version of the algorithm proposed
     by Efford et al. (2004). In outline, the algorithm is

        1.  Find value of sigma that predicts the observed mean
           recapture distance d-bar (see dbar)

        2.  Find value of g0 that, with sigma, predicts the observed
           mean number of captures per individual (by algorithm of
           Efford et al. (2009, Appendix 2))

        3.  Compute the effective sampling area from g0, sigma, using
           thinned mask (see 'esa')

        4.  Compute D = n/esa(g0, sigma), where n is the number of
           individuals detected

     Here 'find' means solve numerically for zero difference between
     the observed and predicted values, using 'uniroot'.

     Computation of d-bar fails if there no recaptures, and all
     returned values are NA.

     A proportion 1-'thin' of the points in the mask may be discarded
     at random to speed execution.

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

     A list of parameter values : 

      D : Density (animals per hectare)

     g0 : Magnitude (intercept) of detection function 

  sigma : Spatial scale of detection function (m) 

_N_o_t_e:

     'autoini' may in future include an option to use 'RPSV' instead of
     'dbar'.

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

     Murray Efford murray.efford@otago.ac.nz

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

     Efford, M. G., Dawson, D. K. and Robbins C. S. (2004) DENSITY:
     software for analysing capture-recapture data from passive
     detector arrays. _Animal Biodiversity and Conservation_ *27*,
     217-228. 

     Efford, M. G., Dawson, D. K. and Borchers, D. L. (2009) Population
     density estimated from locations of individuals on a passive
     detector array. _Ecology_ *90*, 2676-2682.

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

     'capthist', 'mask', 'secr.fit', 'dbar'

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

     demotraps <- make.grid()
     demomask <- make.mask(demotraps)
     demoCH <- sim.capthist (demotraps, popn = list(D = 5, buffer = 100))
     autoini (demoCH, demomask) 

