confint                package:stats                R Documentation

_C_o_n_f_i_d_e_n_c_e _I_n_t_e_r_v_a_l_s _f_o_r _M_o_d_e_l _P_a_r_a_m_e_t_e_r_s

_D_e_s_c_r_i_p_t_i_o_n:

     Computes confidence intervals for one or more parameters in a
     fitted model.  There is a default and a method for objects
     inheriting from class '"lm"'.

_U_s_a_g_e:

     confint(object, parm, level = 0.95, ...)

_A_r_g_u_m_e_n_t_s:

  object: a fitted model object.

    parm: a specification of which parameters are to be given
          confidence intervals, either a vector of numbers or a vector
          of names.  If missing, all parameters are considered.

   level: the confidence level required.

     ...: additional argument(s) for methods.

_D_e_t_a_i_l_s:

     'confint' is a generic function.  The default method assumes
     asymptotic normality, and needs suitable 'coef' and 'vcov' methods
     to be available.  The default method can be called directly for
     comparison with other methods.

     For objects of class '"lm"' the direct formulae based on t values
     are used.

     There are stub methods for classes '"glm"' and '"nls"' which
     invoke those in package 'MASS' which are based on profile
     likelihoods.

_V_a_l_u_e:

     A matrix (or vector) with columns giving lower and upper
     confidence limits for each parameter. These will be labelled as
     (1-level)/2 and 1 - (1-level)/2 in % (by default 2.5% and 97.5%).

_S_e_e _A_l_s_o:

     'confint.glm' and 'confint.nls' in package 'MASS'.

_E_x_a_m_p_l_e_s:

     fit <- lm(100/mpg ~ disp + hp + wt + am, data=mtcars)
     confint(fit)
     confint(fit, "wt")

     ## from example(glm) (needs MASS to be present on the system)
     counts <- c(18,17,15,20,10,20,25,13,12)
     outcome <- gl(3,1,9); treatment <- gl(3,3)
     glm.D93 <- glm(counts ~ outcome + treatment, family=poisson())
     confint(glm.D93)
     confint.default(glm.D93)  # based on asymptotic normality