1d:T7cc,# SN-based test statistic segmentation plot for univariate, mulitivariate and high-dimensional time series The function `max_SNsweep` allows users to compute and plot the SN-based test statistics along with the identified change-points from functions SNSeg_Uni, SNSeg_Multi, or SNSeg_HD. ```r max_SNsweep(SN_result, plot_SN = TRUE, est_cp_loc = TRUE, critical_loc = TRUE) ``` ## Arguments - `SN_result`: The output of functions SNSeg_Uni, SNSeg_Multi or SNSeg_HD. - `plot_SN`: A boolean value to return an SN-based segmentation plot if plot_SN = TRUE. - `est_cp_loc`: A boolean value to plot a red solid vertical line for estimated change-point locations if est_cp_loc = TRUE. - `critical_loc`: A boolean value to plot a blue dashed horizontal line for the critical value if critical_loc = TRUE ## Returns Returns a vector of numeric values of calculated SN-based statistics for each time point. It also generates a SN-based test statistics segmentation plot with the estimated change-points. For more examples of `max_SNsweep` please see the SNSeg vignette: `vignette("SNSeg", package = "SNSeg")` ## Examples ```r set.seed(7) n <- 2000 reptime <- 2 cp_sets <- round(n*c(0,cumsum(c(0.5,0.25)),1)) mean_shift <- c(0.4,0,0.4) rho <- -0.7 ts <- MAR(n, reptime, rho) no_seg <- length(cp_sets)-1 for(index in 1:no_seg){ tau1 <- cp_sets[index]+1 tau2 <- cp_sets[index+1] ts[tau1:tau2,] <- ts[tau1:tau2,] + mean_shift[index] } ts <- ts[,2] result <- SNSeg_Uni(ts, paras_to_test = "mean", confidence = 0.9, grid_size_scale = 0.05, grid_size = 116, plot_SN = FALSE, est_cp_loc = FALSE) # Generate SN-based test statistic segmentation plot # To get the computed SN-based statistics, please run the command "test_stat" test_stat <- max_SNsweep(result, plot_SN = TRUE, est_cp_loc = TRUE, critical_loc = TRUE) # For more examples of \code{max_SNsweep} see the help vignette: # \code{vignette("SNSeg", package = "SNSeg")} ```

max_SNsweep function