daystoyears             package:pastecs             R Documentation

_C_o_n_v_e_r_t _t_i_m_e _u_n_i_t_s _f_r_o_m "_d_a_y_s" _t_o "_y_e_a_r_s" _o_r _b_a_c_k

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

     Convert time scales. The time scale "days" corresponds to 1 unit
     per day. The time scale "years" uses 1 unit for 1 year. It is used
     in any analysis that requires seasonal decomposition and/or
     elimination.

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

     daystoyears(x, datemin=NULL, dateformat="m/d/Y")
     yearstodays(x, xmin=NULL)

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

       x: A vector of time values 

 datemin: A character string representing the first date, using a
          format corresponding to 'dateformat'. For instance, with
          'datemin="04/23/1998"' and 'dateformat="m/d/Y"', the first
          observation is assumed to be made the 23th April 1998. In R,
          it can also be a POSIXt date (see '?DataTimeClasses'). In
          this case, 'dateformat' is not required and is ignored. By
          default, 'datemin=NULL' 

dateformat: The format used for the date in 'datemin'. For instance,
          '"d/m/Y"' or '"m/d/y"'. The distinction between "Y" and "y"
          is not important in Splus, but it is vital in R to use "y"
          for two-digit years (ex: 89) and "Y" for four-digits years
          (ex: 1989), or the date will not be correctly converted! In
          R, you can also use a POSIXt format specification like
          "%d-%m%Y" for instance (see '?strptime' for a complete
          description of POSIXt format specification. In both Splus and
          R, you can also use "mon" for abbreviated months like "mon d
          Y" for "Apr 20 1965", and "month" for fully-spelled months
          like "d month Y" for "24 September 2003" 

    xmin: The minimum value for the "days" time-scale 

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

     The "years" time-scale uses one unit for each year. We
     deliberately "linearized" time in this time-scale and each year is
     considered to have exactly 365.25 days. There is thus no
     adjustment for lep years. Indeed, a small shift (less than one
     day) is introduced. This could result, for some dates, especially
     the 31st December, or 1st January of a year to be considered as
     belonging to the next, or previous year, respectively! Similarly,
     one month is considered to be 1/12 year, no mather if it has 28,
     29, 30 or 31 days. Thus, the same warning applies: there are
     shifts in months introduced by this linearization of time! This
     representation simplifies further calculations, especially
     regarding seasonal effects (a quarter is exactly 0.25 units for
     instance), but shifts introduced in time may or may not be a
     problem for your particular application (if exact dates matters,
     do not use this; if shifts of up to one day is not significant,
     there is no problem, like when working on long-term biological
     series with years as units). Notice that converting it back to
     "days", using 'yearstodays()' restablishes exact dates without
     errors. So, no data is lost, it just a conversion to a simplified
     (linearized) calendar!

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

     A numerical vector of the same length as 'x' with the converted
     time-scale

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

     Philippe Grosjean (phgrosjean@sciviews.org), Frdric Ibanez
     (ibanez@obs-vlfr.fr)

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

     'buysbal'

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

     # A vector with a "days" time-scale (25 values every 30 days)
     A <- (1:25)*30
     # Convert it to a "years" time-scale, using 23/05/2001 (d/m/Y) as first value
     B <- daystoyears(A, datemin="23/05/2001", dateformat="d/m/Y")
     B
     # Convert it back to "days" time-scale
     yearstodays(B, xmin=30)

     # Here is an example showing the shift introduced, and its consequence:
     C <- daystoyears(unclass(as.Date(c("1970-1-1","1971-1-1","1972-1-1","1973-1-1"),
             format = "%Y-%m-%d")))
     C

