normal_switch_xts: Process Data under Normal Conditions

In gabrielodom/mvMonitoring: Multi-State Adaptive Dynamic Principal Component Analysis for Multivariate Process Monitoring

Process Data under Normal Conditions

Description

Three-feature, three-state simulated process data under normal operating conditions as example data for different included functions.

Usage

normal_switch_xts

Format

An xts data matrix with 10080 rows and four columns, corresponding to one week worth of data recorded at a 1-minute interval, and four columns as defined here:

state –

the state indicator for the multivariate system, with three levels

x :

x(t) = t + error

y :

y(t) = t ^ 2 - 3t + error

z :

z(t) = - t ^ 3 + 3t ^ 2 + error

where t is a 10080-entry vector of autocorrelated and non-stationary hidden process realizations. The states alternate each hour and are defined as follows:

State1 –

As presented

State2 –

Rotated by (yaw = 0, pitch = 90, roll = 30) and scaled by (1 * x, 0.5 * y , 2 * z).

State3 –

Rotated by (yaw = 90, pitch = 0, roll = -30) and scaled by (0.25 * x, 0.1 * y , 0.75 * z).

See the vignette for more details.

Source

Simulated in R.

gabrielodom/mvMonitoring documentation built on Nov. 23, 2023, 6:39 p.m.