fractalBlock {fractal} | R Documentation |
Class constructor for fractalBlock
.
fractalBlock(domain,estimator, exponent, exponent.name, scale, stat, stat.name, detrend, overlap, data.name, sum.order, series, logfit, sdf=NULL)
domain |
character string defining the domain in which the calculations took place, e.g., in the time or frequency domain. |
estimator |
character string briefly describing the estimator. |
exponent |
numerical value representing the scaling exponent. |
exponent.name |
character string defining the name of the scaling exponent. |
scale |
numeric vector containing the scales used in the analysis. |
stat |
numeric vector containing the statistic calculated in the analysis. |
stat.name |
character vector describing the name for the calculated statistic. |
detrend |
character string describing any series detrending used as a preprocessive measure.
NULL values are allowed and signify no detrending. |
overlap |
numeric value on [0,1] defining the fraction of overlap used in adjacent blocks of data during the aggregation process. |
data.name |
character string defining the name of the input series. |
sum.order |
integer representing the sum order. |
series |
a numeric vector containing the input series. |
logfit |
a linear regression model (such as that output by lm , lmsreg , or ltsreg )
containing the regression model of the log(scale) versus log(stat) data. |
sdf |
spectral density function. Default: NULL . |
par
. Default: 1.par
. Default: 2.par
. Default: 18.par
for a plot of the data. the first two elements are
used to color the data and the regression line, respectively. Default: c(1,8)
.par
) for the data and regression line plot, respectively. Default: c(1,1)
.grid=list(lty=2, col=16, density=3), key=TRUE, add=FALSE, cex=1, ...)
.par
function).prettPrintList
. Default: "left"
.prettyPrintList
. Default: ":"
.prettyPrintList
. Default: 5.prettyPrintList
function).
## construct a fractalBlock object xvar <- 2^(1:10) yvar <- 0.3^(1:10) z <- fractalBlock(domain="time", estimator="estimator", exponent=pi, exponent.name="PI", scale=xvar, stat=yvar, stat.name="My Stat", detrend=NULL, overlap=0.2, data.name="My Series", sum.order=-1, series=rnorm(2^10), logfit=lm(y ~ x, data=data.frame(x=log(xvar), y=log(yvar)))) ## print the result print(z) ## plot the result plot(z)