plot.HoltWinters            package:stats            R Documentation

_P_l_o_t _f_u_n_c_t_i_o_n _f_o_r _H_o_l_t_W_i_n_t_e_r_s _o_b_j_e_c_t_s

_D_e_s_c_r_i_p_t_i_o_n:

     Produces a chart of the original time series along with the fitted
     values. Optionally, predicted values (and their confidence bounds)
     can also be plotted.

_U_s_a_g_e:

     ## S3 method for class 'HoltWinters':
     plot(x, predicted.values = NA, intervals = TRUE,
             separator = TRUE, col = 1, col.predicted = 2,
             col.intervals = 4, col.separator = 1, lty = 1,
             lty.predicted = 1, lty.intervals = 1, lty.separator = 3,
             ylab = "Observed / Fitted",
             main = "Holt-Winters filtering",
             ylim = NULL, ...)

_A_r_g_u_m_e_n_t_s:

       x: Object of class '"HoltWinters"'

predicted.values: Predicted values as returned by 'predict.HoltWinters'

intervals: If 'TRUE', the prediction intervals are plotted (default).

separator: If 'TRUE', a separating line between fitted and predicted
          values is plotted (default).

col, lty: Color/line type of original data (default: black solid).

col.predicted, lty.predicted: Color/line type of fitted and predicted
          values (default: red solid).

col.intervals, lty.intervals: Color/line type of prediction intervals
          (default: blue solid).

col.separator, lty.separator: Color/line type of observed/predicted
          values separator (default: black dashed).

    ylab: Label of the y-axis.

    main: Main title.

    ylim: Limits of the y-axis. If 'NULL', the range is chosen such
          that the plot contains the original series, the fitted
          values, and the predicted values if any.

     ...: Other graphics parameters.

_A_u_t_h_o_r(_s):

     David Meyer David.Meyer@wu-wien.ac.at

_R_e_f_e_r_e_n_c_e_s:

     C. C. Holt (1957) Forecasting seasonals and trends by
     exponentially weighted moving averages, ONR Research Memorandum,
     Carnigie Institute 52.

     P. R. Winters (1960) Forecasting sales by exponentially weighted
     moving averages, _Management Science_ *6*, 324-342.

_S_e_e _A_l_s_o:

     'HoltWinters', 'predict.HoltWinters'