Nothing
# Set up the data objects used in the examples
examples <- "c:\\Program Files\\Insightful\\Splus70\\fdaS\\examples\\"
# ------------ gait --------------------------
hip <- matrix(scan(paste(examples,"gait\\hip.dat",sep=""), 0), 20, 39)
knee <- matrix(scan(paste(examples,"gait\\knee.dat",sep=""), 0), 20, 39)
# set up the argument values
gaittime <- (1:20)/21
gaitrange <- c(0,1)
# set up a three-dimensional array of function values
gaitarray <- array(0, c(20, 39, 2))
dimnames(gaitarray) <- list(NULL, NULL, c("Hip Angle", "Knee Angle"))
gaitarray[,,1] <- hip
gaitarray[,,2] <- knee
# ------------ goods index --------------------------
temp <- matrix(scan(paste(examples,"goodsindex\\nondurprod.dat",sep=""),0), 18, 81)
tempmat <- temp[2:13,]
tempmat[12,81] <- 0
nondurables <- matrix(tempmat, 12*81, 1)
nondurables <- nondurables[1:971]
ndur <- 971
# for completeness, make dec 99 equal to dec 98, jan 00 equal to jan 99
nondurables <- c(nondurables,nondurables[961])
nondurables <- c(nondurables,nondurables[962])
ndur <- 973
# set up time values
durtime <- (0:(ndur-1))/12 + 1919
goodsrange <- c(1919,2000)
# compute log nondurables
lognondur <- log10(nondurables)
# ------------ Berkeley growth --------------------------
ncasem <- 39
ncasef <- 54
nage <- 31
hgtm <- t(matrix(scan(paste(examples,"growth\\hgtm.dat",sep="") ,0), ncasem, nage, byrow=T))
hgtf <- t(matrix(scan(paste(examples,"growth\\hgtf.dat",sep="") ,0), ncasem, nage, byrow=T))
age <- c( seq(1, 2, 0.25), seq(3, 8, 1), seq(8.5, 18, 0.5))
# ------------ handwriting --------------------------
temp <- array(scan(paste(examples,"handwrit\\fdareg.dat",sep=""),0), c(20,2,1401))
# set up a three-dimensional array
fdaarray <- array(0, c(1401, 20, 2))
fdaarray[,,1] <- t(temp[,1,])/1000
fdaarray[,,2] <- t(temp[,2,])/1000
dimnames(fdaarray) <- list(NULL, NULL, c("X", "Y") )
# Set up time values and range.
# It is best to choose milliseconds as a time scale
# in order to make the ratio of the time
# unit to the inter-knot interval not too
# far from one. Otherwise, smoothing parameter values
# may be extremely small or extremely large.
fdatime <- seq(0, 2300, len=1401)
# ------------ lip --------------------------
lipmat <- matrix(scan(paste(examples,"lip\\lip.dat",sep=""), 0), 51, 20)
liptime <- seq(0,1,.02)
# ------------ melanoma --------------------------
tempmat <- t(matrix(scan(paste(examples,"melanoma\\melanoma.dat",sep=""), 0), 3, 37))
year <- tempmat[,2]
mela <- tempmat[,3]
nyear <- length(year)
# ------------ pinch --------------------------
pinchmat <- matrix(scan(paste(examples,"pinch\\pinch.dat",sep=""),0), 151, 20, byrow=T)
pinchtime <- seq(0,150,len=151)/600
# ------------ refinery --------------------------
refinery <- t(matrix(scan(paste(examples,"refinery\\refinery.dat",sep=""), 0), 3, 193))
tval <- refinery[,1] # observation time
uval <- refinery[,2] # reflux flow
yval <- refinery[,3] # tray 47 level
# center the data on mean values prior to change
uval <- uval - mean(uval[1:60])
yval <- yval - mean(yval[1:60])
# ------------ daily weather --------------------------
tempav <- matrix(scan(paste(examples,"weather\\dailtemp.dat",sep=""),0), 365, 35)
precav <- matrix(scan(paste(examples,"weather\\dailprec.dat",sep=""),0), 365, 35)
# set up the times of observation at noon
daytime <- (1:365)-0.5
dayrange <- c(0,365)
dayperiod <- 365
# day values roughly in weeks
weeks <- seq(0,365,length=53)
# define 11-character names for stations
place <- c(
"Arvida ", "Bagottville", "Calgary ", "Charlottvl ", "Churchill ", "Dawson ",
"Edmonton ", "Fredericton", "Halifax ", "Inuvik ", "Iqaluit ", "Kamloops ",
"London ", "Montreal ", "Ottawa ", "Pr. Albert ", "Pr. George ", "Pr. Rupert ",
"Quebec ", "Regina ", "Resolute ", "Scheffervll", "Sherbrooke ", "St. Johns ",
"Sydney ", "The Pas ", "Thunderbay ", "Toronto ", "Uranium Cty", "Vancouver ",
"Victoria ", "Whitehorse ", "Winnipeg ", "Yarmouth ", "Yellowknife")
dimnames(tempav) <- list(NULL,place)
dimnames(precav) <- list(NULL,place)
# set up indices that order the stations from east to west to north
geogindex <- c(24, 9, 25, 34, 4, 8, 22, 1, 2, 19, 23, 14, 15, 28, 13,
27, 33, 26, 5, 20, 16, 29, 7, 3, 12, 30, 31, 17, 18, 32,
6, 35, 11, 10, 21)
# put the stations in geographical order, from east to west to north
# rather in the original alphatical order.
tempav <- tempav[,geogindex]
precav <- precav[,geogindex]
place <- place[geogindex]
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