fmri_ts_forecast: forecast the fMRI data based on the time series

In TCIU: Spacekime Analytics, Time Complexity and Inferential Uncertainty

forecast the fMRI data based on the time series

Description

a function to forecast the fMRI data based on the time series

Usage

fmri_ts_forecast(fmridata, voxel_location, cut = 10)

Arguments

fmridata	a 4D array contains information for the fMRI spacetime image. The data should only contain the magnitude for the fMRI image.
voxel_location	a 3d array indicating the voxel location of the brain
cut	breaking point of the time-series data. The default is 10.

Details

The function fmri_ts_forecast is used to forecast with time series. It will fit the best ARIMA model to univariate time series from the input fMRI data.

Value

a figure forecasting the fMRI voxel with time series

Author(s)

SOCR team <http://socr.umich.edu/people/>

Examples

fmri_generate = fmri_simulate_func(dim_data = c(64, 64, 40), mask = mask)

smoothmod <- GaussSmoothArray(fmri_generate$fmri_data, sigma = diag(3,3))
fmri_ts_forecast(smoothmod,c(41,44,33))

TCIU documentation built on Oct. 6, 2023, 5:09 p.m.