

   CCrreeaattee aa rreessppoonnssee oobbjjeecctt

        restovec(response, times=NULL, nest=NULL, coordinates=NULL,
             censor=NULL, totals=NULL, weights=NULL, delta=NULL, type=NULL)

   AArrgguummeennttss::

   response: A matrix or dataframe of response values, a list
             of vectors of event histories, or a list of one or
             more column matrices, for each individual, with
             response values in the first column and times in
             the second, possibly followed by columns with
             nesting categories, binomial totals, censoring
             indicators, and/or units of measurement. For inde-
             pendent responses with one observation per indi-
             vidual or for a single time series, one vector may
             be supplied (in the latter case, the times must be
             given even if equally spaced).

      times: When response is a matrix, a vector of possibly
             unequally spaced times when they are the same for
             all individuals or a matrix of times. Not neces-
             sary if equally spaced, except if a vector con-
             taining a single time series is supplied (if not
             given in this case, it considers the responses to
             be independent, not a time series). For clustered
             data with no time ordering, set to FALSE.

       nest: When `response' is a matrix, a vector of length
             equal to the number of responses per individual
             indicating which responses belong to which nesting
             category. Values must be consecutive increasing
             integers. This is the second level of nesting,
             with the individual being the first level.

   coordinates: When `response' is a vector, a two-column
             matrix giving the coordinates for spatial data.

     censor: A vector of the same length as the number of indi-
             viduals containing a binary indicator, with a one
             indicating that the last time period in the series
             terminated with an event and zero that it was cen-
             sored, or, when response is matrix, a matrix of
             the same size.  For event history data, even with
             no censoring, an appropriate vector of ones must
             be supplied.

     totals: If the response is a matrix of binomial counts, a
             corresponding vector (one total or one per indi-
             vidual) or matrix of totals.

    weights: A vector, matrix, or list of vectors of frequen-
             cies or weights, of the same dimensions as the
             response.

      delta: The unit of measurement (if not equal to unity), a
             scalar or a vector. If the response has been
             transformed, this should contain the numerical
             values of the Jacobian. When the `transform'
             method is applied to the response, this is auto-
             matically updated.

       type: The type of measurement: nominal, ordinal, dis-
             crete, duration, continuous, or unknown. This
             becomes an attribute of the `response' object.

   DDeessccrriippttiioonn::

        `restovec' produces an object of class, response, from
        a list of vectors of event histories or of two or more
        column matrices with times, response values, and possi-
        bly binomial totals, nesting categories, censor indica-
        tors, and/or units of measurement, for each individual,
        or a matrix or dataframe of response values.

        Such objects can be printed and plotted. NAs are
        removed with `rmna' (where necessary, incoordination
        with the appropriate covariates).

        Methods are available for extracting the response, the
        numbers of observations per individual, the times, the
        weights, and the nesting variable: `response', `nobs',
        `times', `weights', and `nesting'. The response and or
        the times may be transformed using `transform(z,
        y=fcn1(y), times=fcn2(times))' where fcn1 and fcn2 are
        transformations. When the response is transformed, the
        Jacobian is automatically calculated.

   VVaalluuee::

        Returns an object of class, response, containing a vec-
        tor with the responses (z$y), a corresponding vector of
        times (z$times) if applicable, a vector giving the num-
        ber of observations per individual (z$nobs, set to a
        scalar 1 if observations are independent), and possibly
        binomial totals (z$n), nesting (clustering, z$nest),
        censoring (z$censor), weights (z$wt), and unit of mea-
        surement information (z$delta).

   AAuutthhoorr((ss))::

        J.K. Lindsey

   SSeeee AAllssoo::

        `read.list', `rmna', `tcctomat', `transform', `tvc-
        tomat'.

   EExxaammpplleess::

        y <- matrix(rnorm(20),ncol=5)
        # times assumed to be 1:5
        restovec(y)
        #unequally-spaced times
        tt <- c(1,3,6,10,15)
        print(resp <- restovec(y,times=tt))
        response(resp)
        response(resp, nind=2:3)
        times(resp)
        nobs(resp)
        weights(resp)
        nesting(resp)
        # because individuals are the only nesting, this is the same as
        covind(resp)
        # binomial
        y <- matrix(rpois(20,5),ncol=5)
        # responses summarized as relative frequencies
        print(respb <- restovec(y,totals=y+matrix(rpois(20,5),ncol=5),times=tt))
        response(respb)
        # censored data
        y <- matrix(rweibull(20,2,5),ncol=5)
        print(respc <- restovec(y,censor=matrix(rbinom(20,1,0.9),ncol=5),times=tt))
        # if there is no censoring, censor indicator is not printed
        response(respc)
        # nesting clustered within individuals
        nest <- c(1,1,2,2,2)
        print(respn <- restovec(y,censor=matrix(rbinom(20,1,0.9),ncol=5),
             times=tt,nest=nest))
        response(respn)
        times(respn)
        nesting(respn)

