# tscR: Dummy trajectories data In tscR: A time series clustering package combining slope and Frechet distances

## Description

A dataset containing 300 tajectories and 3 time points

## Usage

 `1` ```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:

Simulated data

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15``` ```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") ```

tscR documentation built on Nov. 8, 2020, 5:53 p.m.