tscR: Dummy trajectories data

In fpsanz/tscR: A time series clustering package combining slope and Frechet distances

Description

A dataset containing 300 tajectories and 3 time points

Usage

tscR

Format

A data frame 300 rows and 3 columns:

T1

time interval

T2

time interval

T3

time interval

Details

This dataset has been created specifically to be able to illustrate the operation of the package with different distance metrics. Thus, from 3-4 hand-created trajectories (ascending, descending, quasi-horizontal) we have generated 300 trajectories with random variations from the original ones. The code used was similar to the one attached here:

Source

Simulated data

Examples

df <- data.frame(T1 = c(4,3.9,4.1,4), 
                 T2=c(5.5, 4.3, 3.7, 2.5),
                 T3 = c(7, 3.9,4.1, 1))
df1 <- matrix(NA, nrow=100, ncol=3)
df2 <- matrix(NA, nrow=100, ncol=3)
df3 <- matrix(NA, nrow=100, ncol=3)
df4 <- matrix(NA, nrow=100, ncol=3)
for(i in seq(1,75)){
 df1[i,] <- jitter(as.numeric(df[1,]), factor = 2.5)
 df2[i,] <- jitter(as.numeric(df[2,]), factor = 7.5)
 df3[i,] <- jitter(as.numeric(df[3,]), factor = 7.5)
 df4[i,] <- jitter(as.numeric(df[4,]), factor = 2.5)
}
df <- as.data.frame(rbind(df1,df2,df3, df4))
names(df) <- c("T1","T2","T3")

fpsanz/tscR documentation built on July 17, 2020, 2:20 a.m.