Rfssa (version 2.1.0)

eval.fts: Functional Time Series Evaluation

Description

This is a method that can be used to evaluate a functional time series (fts) object at new, specified grid points.

Usage

eval.fts(Y, grid, ud_basis = NULL)

Value

A list of length p of matrices or three-dimensional arrays where each list entry type depends on whether the variable is observed over a one or two-dimensional domain.

Arguments

Y

An object of class fts to be evaluated.

grid

A list of length p where each entry is a numeric, matrix, list, or NULL specifying the grid to evaluate the variable over. If the entry is NULL, then the variable is evaluated over the original grid.

ud_basis

A list of length p where each entry is a matrix specifying the user-defined basis to be used for the evaluation of a variable. Note that the specified basis should match with the basis used to estimate the fts object in type and dimension.

Examples

if (FALSE) {
## Evaluate a univariate FTS at less grid points
require(Rfssa)
load_github_data("https://github.com/haghbinh/Rfssa/blob/master/data/Callcenter.RData")
## Define functional objects
D <- matrix(sqrt(Callcenter$calls), nrow = 240)
N <- ncol(D)
time <- substr(seq(ISOdate(1999, 1, 1), ISOdate(1999, 12, 31), by = "day"),1,10)
K <- nrow(D)
u <- seq(0, K, length.out = K)
d <- 22 # Optimal Number of basis elements
## Define functional time series
Y <- Rfssa::fts(list(D), list(list(d, "bspline")), list(u),time)
plot(Y, mains = c("Call Center Data Line Plot"),
xlabels = "Time (6 minutes aggregated)",
ylabels = "Sqrt of Call Numbers",type="line",
xticklabels = list(c("00:00","06:00","12:00","18:00","24:00")),xticklocs =
 list(c(1,60,120,180,240)))
u <- seq(0,K,length.out = 48)
D = eval.fts(Y=Y,grid = list(u))
Y <- Rfssa::fts(D, list(list(d, "bspline")), list(u))
plot(Y, mains = c("Call Center Data Line Plot"),
xlabels = "Time (6 minutes aggregated)",
ylabels = "Sqrt of Call Numbers",type="line",
xticklabels = list(c("00:00","06:00","12:00","18:00","24:00")),xticklocs =
 list(c(1,12,24,36,48)))

## Evaluate a multivariate FTS at more grid points

require(Rfssa)
load_github_data("https://github.com/haghbinh/Rfssa/blob/master/data/Montana.RData")
Temp <- Montana$Temp
NDVI <- Montana$NDVI
d_temp <- 11
d_NDVI <- 13
## Define functional time series
Y <- Rfssa::fts(
  list(Temp / sd(Temp), NDVI), list(
    list(d_temp, "bspline"),
    list(d_NDVI, d_NDVI, "bspline", "bspline")
  ),
  list(c(0, 23), list(c(1, 33), c(1, 33))),
time=colnames(Temp))
# Plot the first 100 observations
plot(Y[1:100],
     xlabels = c("Time", "Longitude"),
     ylabels = c("Standardized Temperature (\u00B0C)", "Latitude"),
     zlabels = c("", "NDVI"),
     mains = c("Temperature Curves", "NDVI Images"), color_palette = "RdYlGn",
     xticklabels = list(c("00:00","06:00","12:00","18:00","24:00"),
     c("113.40\u00B0 W", "113.30\u00B0 W")),xticklocs =
       list(c(1,6,12,18,24),c(1,33)),
       yticklabels = list(NA,c("48.70\u00B0 N", "48.77\u00B0 N")),yticklocs =
       list(NA,c(1,33))
)

grid_temp = seq(0,23,length.out = 100)
u_NDVI = seq(1,33,length.out = 100)
v_NDVI = seq(1,33,length.out = 100)
grid_NDVI = list(u_NDVI,v_NDVI)
D = eval.fts(Y = Y, grid = list(grid_temp, grid_NDVI))

Y <- Rfssa::fts(
  D, list(
    list(d_temp, "bspline"),
    list(d_NDVI,d_NDVI,"bspline","bspline")
  ),
  list(grid_temp, grid_NDVI)
)

plot(Y[1:100],
     xlabels = c("Time", "Longitude"),
     ylabels = c("Standardized Temperature (\u00B0C)", "Latitude"),
     zlabels = c("", "NDVI"),
     mains = c("Temperature Curves", "NDVI Images"), color_palette = "RdYlGn",
     xticklabels = list(c("00:00","06:00","12:00","18:00","24:00"),
     c("113.40\u00B0 W", "113.30\u00B0 W")),xticklocs =
       list(c(1,24,48,72,100),c(1,33)),
       yticklabels = list(NA,c("48.70\u00B0 N", "48.77\u00B0 N")),yticklocs =
       list(NA,c(1,33))
)

}