Predict fqpca scores — predict.fqpca

S3 method for class 'fqpca_object' Given a new matrix Y, predicts the value of the scores associated to the given matrix.

Usage

# S3 method for class 'fqpca_object'
predict(object, newdata, ...)

Arguments

object: An object output of the fqpca function.
newdata: The N by T matrix of observed time instants to be tested, or the dataframe storing the tf functional vector using the same colname as the one used in the fqpca function.
...: further arguments passed to or from other methods.

Value

The predicted matrix of scores.

Examples


n.obs = 150
n.time = 144

# Generate scores
c1.vals = rnorm(n.obs)
c2.vals = rnorm(n.obs)

# Generate pc's
pc1 = sin(seq(0, 2*pi, length.out = n.time))
pc2 = cos(seq(0, 2*pi, length.out = n.time))

# Generate data
Y <- c1.vals * matrix(pc1, nrow = n.obs, ncol=n.time, byrow = TRUE) +
c2.vals * matrix(pc2, nrow = n.obs, ncol=n.time, byrow = TRUE)

# Add noise
Y <- Y + matrix(rnorm(n.obs * n.time, 0, 0.4), nrow = n.obs)

# Add missing observations
Y[sample(n.obs*n.time, as.integer(0.2*n.obs*n.time))] <- NA

results <- fqpca(data = Y, npc = 2, quantile.value = 0.5, seed=1)

predictions <- predict(object = results, newdata = Y[101:150,])