timesboot (version 1.0)

boot_spec: Function that computes boostrapped confidence intervals for the sample periodogram.

Description

The function resamples a time series object using phase scramble bootstrap and returns the average,lower and upper confidence bounds.

Usage

boot_spec(series, replic = 5000, spansa = c(11, 21), 
plot = TRUE, de_trend = FALSE, alpha = 0.05)

Arguments

series

A time series object

replic

The amount of replications used in the bootstrap step

spansa

The spans for smoothing the spectrum

plot

TRUE,FALSE. Whether plotting is desired. Default is TRUE.

de_trend

TRUE,FALSE. Should de-trending be applied to the series.Default is FALSE

alpha

The alpha used in the construction of the CI. Default is 0.05

Value

average

The average value for each frequency

upper

The upper value for each frequency

lower

The lower value for each frequency

Examples

boot_spec(AirPassengers,replic=1000,alpha=0.05)

function (series, replic = 5000, spansa = c(11, 21), plot = TRUE, 
    de_trend = FALSE, alpha = 0.05) 
{
    if (is.ts(series) == TRUE) {
    	library(boot)
        kas = tsboot(series, redraw, p = spansa, detrend = de_trend, 
            replic, sim = "scramble")
        span1 = spansa[1]
        span2 = spansa[2]
        quantiles = matrix(0, length(kas$t[1, ]), 3)
        Xvalues = spec.pgram(series, spans = c(span1, span2), 
            plot = FALSE)
        for (i in 1:length(kas$t[1, ])) {
            cp = kas$t[, i]
            quantiles[i, 1] = quantile(cp, alpha)
            quantiles[i, 2] = quantile(cp, 1 - alpha/2)
            quantiles[i, 3] = mean(cp)
        }
        if (plot == TRUE) {
            maximus = max(quantiles[, 3])
            plot(Xvalues$freq, quantiles[, 1], type = "l", col = "blue", 
                ylim = c(0, maximus * 2), main = "Bootstraped Periodogram", 
                ylab = "periodogram", lwd = 1, xlab = "frequency")
            polygon(c(Xvalues$freq, rev(Xvalues$freq)), c(quantiles[, 
                1], rev(quantiles[, 2])), col = "skyblue")
            lines(Xvalues$freq, quantiles[, 3], type = "o", col = "black", 
                pch = 20)
        }
        lix = list(freq = Xvalues$freq, upper = quantiles[, 2], 
            lower = quantiles[, 1], mean = quantiles[, 3])
        return(lix)
    }
    else {
        return("Object is not a time-series")
    }
  }