profileCI              package:Rcapture              R Documentation

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

     The 'profileCI' function computes the multinomial profile
     likelihood for the adundance of some closed population
     capture-recapture models.

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

     profileCI(X, dfreq=FALSE, m="M0", h="Chao", a=2, mX=NULL, 
               mname="Customized model", neg=TRUE, alpha=0.05)

     ## S3 method for class 'profileCI':
     print(x, ...)

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

       X: The table of the observed capture histories in one of the two
          accepted formats. In the default format, it has one row per
          unit captured in the experiment. In this case, the number of
          columns in the table represents the number of capture
          occasions in the experiment (noted t). In the alternative
          format, it contains one row per capture history followed by
          its frequency. In that case, 'X' has t+1 columns. The first t
          columns of 'X', identifying the capture histories, must
          contain only zeros and ones. The number one indicates a
          capture. 

   dfreq: This argument specifies the format of the data matrix 'X'. By
          default, it is set to FALSE, which means that 'X' has one row
          per unit. If it is set to TRUE, then the matrix 'X' contains
          frequencies in its last column.

       m: A character string identifying the  model, either "M0"=M0
          model, "Mt"=Mt model, "Mh"=Mh model or "Mth"=Mth model.

       h: A character string ("Chao", "Poisson" or "Darroch") or a
          numerical 'R' function specifying the form of the column for
          heterogeneity in the design matrix. "Chao" represents Chao's
          model, "Poisson" represents the function f(k)=a^k-1, where k
          is the number of captures, and "Darroch" represents the
          function f(k)=k^2/2. If an 'R' function is given, it is the
          implemantation of any mathematical function f(k). It has only
          one argument.

       a: The value of the exponent's base for a Poisson model. 

      mX: The design matrix of the loglinear model. In this matrix, the
          order of the capture histories is as defined in the
          'histpos.t' function.

   mname: A character string specifying the name of the customized
          model.

     neg: If this option is set to TRUE, negative eta parameters in
          Chao's models are set to zero. 

   alpha: A confidence interval with confidence level 1-alpha is
          constructed. The value of alpha must be between 0 and 1; the
          default is 0.05.  

       x: An object, produced by the 'profileCI' function, to print.

     ...: Further arguments passed to or from other methods.

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

     This function does not work for closed population models featuring
     a behavioral effect, such as Mb and Mbh.

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

     This function produces a plot of the multinomial profile
     likelihood for N. The value of N maximizing the profile likelihood
     and the bounds of the confidence interval are identified. It also
     produces the following objects : 

       n: The number of captured units

 results: A table containing the abundance estimation and its
          confidence interval.

   alpha: 1-the confidence level of the interval.

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

     Sophie Baillargeon sbaillar@mat.ulaval.ca and Louis-Paul Rivest
     lpr@mat.ulaval.ca

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

     Baillargeon, S. and Rivest, L.P. (2007). The Rcapture package:
     Loglinear models for capture-recapture in R. _Journal of
     Statistical Software_, to appear (available online at <URL:
     http://www.jstatsoft.org/>).

     Cormack, R. M. 1992. Interval estimation for mark-recapture
     studies of closed populations. _Biometrics_, *48*, 567-576.

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

     'closedp', 'closedp.mX', 'closedp.h'

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

     data(hare)
     profileCI(hare, m = "Mth", h = "Poisson", a = 2)

     data(HIV)
     mat<-histpos.t(4)
     mX2<-cbind(mat,mat[,1]*mat[,2])
     profileCI(HIV,dfreq=TRUE,mX=mX2,mname="Mt interaction 1,2")

