Package index • tvdsm

All functions

RMSSD(): Compute Root Mean Square of Successive Differences (RMSSD)

TSDescriptivesByCondition(): Alias for descriptivesByCondition

analyzeDyad(): Analyze dyad data for TVDSM analysis

analyzeGroup(): Analyze a group of participant data files

analyzeLags(): Analyze model performance over varying lags

annotate.relative(): Annotate a ggplot with relative coordinates

as.dyad(): Convert Two Participant Data into a Dyad

as.group(): Combine participant data into a group dyad

as.simulateddyad(): Create Simulated Dyad Data

bootstrapSimulation(): Bootstrap Dyadic Simulation

compareSim(): Compare Simulated Signals

compareSimulatedDyads(): Compare Simulated Dyads

describeDyad(): Describe dyad interdependence

descriptivesByCondition(): Descriptives By Condition

distance(): Calculate Euclidean Distance

downsample.eda(): Downsample EDA Data

dsmodel(): Fit Dyadic Model

dsmodel.multilag(): Fit Multi-lag Dyadic Model

dsmodel.sem(): Fit Dyadic Model using SEM

dummyCodeByCondition(): Dummy Code By Condition

dyad.dsgraph(): Plot Dyadic Graph

dyad.dsmodel(): Build Dyadic Model

dynamicalCorrelation(): Compute dynamical correlation using bootstrap methods

examples(): Run Example Simulations

fitDSModel(): Fit a dynamic system model

fitDSModelForDyad(): Fit dynamic system model for dyad data

generateI3Mat(): Generate an I3 matrix for interdependence analysis

get.key(): Extract a key from a list of objects

getFS(): Get Sampling Frequency

ggCaterpillar(): ggCaterpillar: Plot random effects as QQ-plots or caterpillar dotplots.

ggbracket(): Add bracket annotations for statistical comparisons on a ggplot

gghist(): Create a histogram with density and normality annotation

ggrel.x(): Calculate a relative x-coordinate in a ggplot

ggrel.y(): Calculate a relative y-coordinate in a ggplot

interruptedTimeSeries(): Interrupted Time Series Analysis (Not Implemented)

linearTrend(): Compute Linear Trend Slope

lmp(): Calculate p-value from an lm object

makeDyad(): Create Dyad Data Frame

multiplot(): Arrange multiple ggplot objects in a grid

normalize(): Normalize a Numeric Vector

o.Lag(): Compute Lag Difference

o.center(): Center a Numeric Vector

o.coef(): Extract Coefficient with Significance Check

o.estLag(): Estimate Lag with Moving Window

o.rescale(): Rescale a Vector to [0,1]

o.scale(): Scale Vector to [0,1]

o.smooth(): Smooth a Numeric Vector

p.format(): Format p-value for display

pbcopy(): Copy Text to Clipboard

plot(<density>): Plot density contour of beta coefficients

plot(<dsgraph>): Create Plot for Dyadic State Space Graph

plot(<eda>): Plot EDA data with optional accelerometer data

plot(<lagparams>): Plot lag parameters over time

plot(<tvdsm>): Plot TVDSM model results

plotDyad(): Plot dyadic data using ggplot2

plotEDAByCondition(): Plot EDA by Condition

plotMetric(): Plot a metric with grouping and error bars

plotTSDescriptives(): Plot Time Series Descriptive Statistics

plotlyDyad(): Plot dyadic data using Plotly

r2.corr.mer(): Calculate R-squared from a Mixed Effects Model

rand.dyad(): Generate Random Dyadic Data

read.Codes(): Read Condition Codes

read.ERCodes(): Read Engagement Codes

read.IBI(): Read IBI Data from CSV

read.IBI.TS(): Read IBI Time Series Data

read.RTCodes(): Read RTCodes

read.actiwave(): Read Actiwave Data

read.biosync(): Read Biosync Data

read.csvdata(): Read CSV Data with Timestamp Parsing

read.dyad(): Read Dyad Data from File

read.e4(): Read E4 Data

read.eda(): Read EDA Data

read.edf(): Read EDF Data

read.empatica(): Read Empatica Data

read.empatica.acc(): Read Empatica Accelerometer Data

read.empatica.bvp(): Read Empatica BVP Data

read.empatica.eda(): Read Empatica EDA Data

read.ibutton(): Read iButton Data

read.reda(): Read Reda Data

runAnova(): Run ANOVA on model set

runFalsePairings(): Run False Pairings Analysis

sampleSignal(): Sample Signal

save.eda(): Save EDA Data to File

saveDataForGraphing(): Save data for graphing from TVDSM analysis

saveInterpersonalData(): Save interpersonal analysis data to a CSV file

scatter_plot(): Create a scatter plot with a linear fit and correlation annotation

se(): Compute Standard Error of a Vector

simulate(): Simulate Data using Linear Models

simulateDyad(): Simulate a Dyadic Time Series

simulatePartner(): Simulate a Partner Time Series

statespacegraph(): Plot State Space Graph

topography(): Plot Topography Density

tsDescriptives(): Compute Time Series Descriptive Statistics

urlForModel(): Generate URL for model visualization

validateConditionTimes(): Validate condition times within data range

vectorfield(): Create a Vector Flow Plot

vectorflow(): Visualize Vector Field

window(): Apply Moving Window Operation