1d:T7b0,# Standard Deviation of Functional Data Evaluate the standard deviation of a set of functions in a functional data object. ```r sd.fd(fdobj) std.fd(fdobj) stdev.fd(fdobj) stddev.fd(fdobj) ``` ## Arguments - `fdobj`: a functional data object. ## Details The multiple aliases are provided for compatibility with previous versions and with other languages. The name for the standard deviation function in R is 'sd'. Matlab uses 'std'. S-Plus and Microsoft Excal use 'stdev'. 'stddev' was used in a previous version of the 'fda' package and is retained for compatibility. ## Returns a functional data object with a single replication that contains the standard deviation of the one or several functions in the object `fdobj`. ## References Ramsay, James O., Hooker, Giles, and Graves, Spencer (2009), **Functional data analysis with R and Matlab**, Springer, New York. Ramsay, James O., and Silverman, Bernard W. (2005), **Functional Data Analysis, 2nd ed.**, Springer, New York. Ramsay, James O., and Silverman, Bernard W. (2002), **Applied Functional Data Analysis**, Springer, New York. ## See Also `mean.fd`, `sum.fd`, `center.fd` ## Examples ```r liptime <- seq(0,1,.02) liprange <- c(0,1) # ------------- create the fd object ----------------- # use 31 order 6 splines so we can look at acceleration nbasis <- 51 norder <- 6 lipbasis <- create.bspline.basis(liprange, nbasis, norder) lipbasis <- create.bspline.basis(liprange, nbasis, norder) # ------------ apply some light smoothing to this object ------- Lfdobj <- int2Lfd(4) lambda <- 1e-12 lipfdPar <- fdPar(fd(matrix(0,nbasis,1), lipbasis), Lfdobj, lambda) lipfd <- smooth.basis(liptime, lip, lipfdPar)$fd names(lipfd$fdnames) = c("Normalized time", "Replications", "mm") lipstdfd <- sd.fd(lipfd) oldpar <- par(no.readonly=TRUE) plot(lipstdfd) par(oldpar) all.equal(lipstdfd, std.fd(lipfd)) all.equal(lipstdfd, stdev.fd(lipfd)) all.equal(lipstdfd, stddev.fd(lipfd)) ```

sd function