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-
- _F_a_m_i_l_y _O_b_j_e_c_t_s _f_o_r _M_o_d_e_l_s
-
- family(object)
-
- binomial(link=logit)
- gaussian()
- Gamma(link=inverse)
- inverse.gaussian()
- poisson(link=log)
- quasi(link=identity, variance=constant)
-
- _A_r_g_u_m_e_n_t_s:
-
- link : a specification for the model link function.
- The binomial family admits the links; logit,
- probit and cloglog (complementary log-log),
- the Gamma family the links; identity, inverse
- and log, the poisson family the links; iden-
- tity log and sqrt, and the quasi family the
- links; logit, probit, cloglog, identity,
- inverse, log, 1/mu^2 and sqrt. The other
- families have only a single permissible link
- function. These are the identity for the
- gaussian family and 1/mu^2 for the
- inverse.gaussian family. The function power
- can also be used to create a power link func-
- tion for the quasi family.
-
- variance : for all families, other than quasi, the vari-
- ance function is determined by the family.
- The quasi family will accept the specifica-
- tions constant, mu(1-mu), mu, mu^2 and mu^3
- as variance function.
-
- object : the function family accesses the family
- objects which are stored within objects
- created by modelling functions (e.g. glm).
-
- _D_e_s_c_r_i_p_t_i_o_n:
-
- Family objects provide a convenient way to specify the
- details of the models used by functions such as glm.
- See the documentation for glm for the details on how
- such model fitting takes place.
-
- _R_e_f_e_r_e_n_c_e_s:
-
- McCullagh P. and J. A. Nelder (1989). Generalized
- Linear Models. London: Chapman and Hall.
-
- Dobson, A. J. (1983). An Introduction to Statistical
- Modelling. London: Chapman and Hall.
-
- Cox, D. R. and E. J. Snell (1981). Applied Statistics;
- Principles and Examples. London: Chapman and Hall.
-
- _S_e_e _A_l_s_o:
-
- glm, power.
-
-