A B C D E F G H I J L M P Q R S T V W misc
STAR-package | Spike Train Analysis with R |
acf.spikeTrain | Auto- Covariance and -Correlation Function Estimation for Spike Train ISIs |
as.CPSP | Counting Process Sample Paths |
as.repeatedTrain | Coerce and Test repeatedTrain Objects |
as.spikeTrain | Coerce, Test and Extract from spikeTrain Objects |
brt4df | Get Backward Recurrence Times from Data Frames Generated by mkGLMdf |
CAL1S | Spike Trains of several Cockroach Antennal Lobe Neurons Recorded from Six Animals |
CAL1V | Spike Trains of several Cockroach Antennal Lobe Neurons Recorded from Six Animals |
CAL2C | Spike Trains of several Cockroach Antennal Lobe Neurons Recorded from Six Animals |
CAL2S | Spike Trains of several Cockroach Antennal Lobe Neurons Recorded from Six Animals |
changeScale | Change the Scales of a quickPredict Object for an Interaction Term |
coef.durationFit | Utility Functions for durationFit Objects |
compModels | Compare Duration Models on a Specific Data Set |
contour.jpsth | Related Functions and Methods for Joint-PSTHs and Joint Scatter Diagrams |
contour.quickPredict | Graphical Methods for quickPredict Objects |
crossGeneral | Computations of Boundary Crossing Probabilities for the Wiener Process |
crossTight | Computations of Boundary Crossing Probabilities for the Wiener Process |
df4counts | Generates a Data Frame from a repeatedTrain Object After Time Binning |
diff.spikeTrain | diff method for spikeTrain objects |
dinvgauss | The Inverse Gaussian Distribution |
dllogis | The Log Logistic Distribution |
drexp | The Refractory Exponential Distribution |
e060517ionon | Spike Trains of several Cockroach Antennal Lobe Neurons Recorded from Six Animals |
e060517spont | Spike Trains of several Cockroach Antennal Lobe Neurons Recorded from Six Animals |
e060817citron | Spike Trains of several Cockroach Antennal Lobe Neurons Recorded from Six Animals |
e060817mix | Spike Trains of several Cockroach Antennal Lobe Neurons Recorded from Six Animals |
e060817spont | Spike Trains of several Cockroach Antennal Lobe Neurons Recorded from Six Animals |
e060817terpi | Spike Trains of several Cockroach Antennal Lobe Neurons Recorded from Six Animals |
e060824citral | Spike Trains of several Cockroach Antennal Lobe Neurons Recorded from Six Animals |
e060824spont | Spike Trains of several Cockroach Antennal Lobe Neurons Recorded from Six Animals |
e070528citronellal | Spike Trains of several Cockroach Antennal Lobe Neurons Recorded from Six Animals |
e070528spont | Spike Trains of several Cockroach Antennal Lobe Neurons Recorded from Six Animals |
frt | Computes Forward Recurrence Times from Two transformedTrain Objects |
gamlockedTrain | Function to Smooth a lockedTrain Object and Related Methods: The Penalized Regression Spline Approach |
gammaMLE | Maximum Likelihood Parameter Estimation of a Gamma Model with Possibly Censored Data |
gamObj | Generic Function and Methods for Extracting a gamObject |
gamObj.gamlockedTrain | Generic Function and Methods for Extracting a gamObject |
gamObj.gampsth | Generic Function and Methods for Extracting a gamObject |
gampsth | Smooth Peri Stimulus Time Histogram Related Functions and Methods: The Penalized Regression Spline Approach |
gsslockedTrain | Function to Smooth a lockedTrain Object and Related Methods: The Smoothing Spline Approach |
gsslockedTrain0 | Function to Smooth a lockedTrain Object and Related Methods: The Smoothing Spline Approach |
gssObj | Generic Function and Methods for Extracting a gss object |
gssObj.gsslockedTrain | Generic Function and Methods for Extracting a gss object |
gssObj.gsslockedTrain0 | Generic Function and Methods for Extracting a gss object |
gssObj.gsspsth | Generic Function and Methods for Extracting a gss object |
gssObj.gsspsth0 | Generic Function and Methods for Extracting a gss object |
gsspsth | Smooth Peri Stimulus Time Histogram Related Functions and Methods: The Smoothing Spline Approach |
gsspsth0 | Smooth Peri Stimulus Time Histogram Related Functions and Methods: The Smoothing Spline Approach |
hgamma | Hazard Functions for Some Common Duration Distributions |
hinvgauss | Hazard Functions for Some Common Duration Distributions |
hist.lockedTrain | Auto- and Cross-Intensity Function Estimate for Spike Trains |
hllogis | Hazard Functions for Some Common Duration Distributions |
hlnorm | Hazard Functions for Some Common Duration Distributions |
hrexp | Hazard Functions for Some Common Duration Distributions |
hweibull | Hazard Functions for Some Common Duration Distributions |
image.jpsth | Related Functions and Methods for Joint-PSTHs and Joint Scatter Diagrams |
image.quickPredict | Graphical Methods for quickPredict Objects |
invgaussMLE | Maximum Likelihood Parameter Estimation of an Inverse Gaussian Model with Possibly Censored Data |
is.durationFit | Utility Functions for durationFit Objects |
is.repeatedTrain | Coerce and Test repeatedTrain Objects |
is.spikeTrain | Coerce, Test and Extract from spikeTrain Objects |
is.varianceTime | Variance-Time Analysis for Spike Trains |
isi | Get Lagged Inter Spike Intervals (ISIs) From Data Frames Generated by mkGLMdf |
isiHistFit | ISI Histogram With Fitted Model and CI |
jpsth | Related Functions and Methods for Joint-PSTHs and Joint Scatter Diagrams |
jpsth2df | Related Functions and Methods for Joint-PSTHs and Joint Scatter Diagrams |
jsd | Related Functions and Methods for Joint-PSTHs and Joint Scatter Diagrams |
lines.CountingProcessSamplePath | Counting Process Sample Paths |
lines.FirstPassageTime | Computations of Boundary Crossing Probabilities for the Wiener Process |
lines.quickPredict | Graphical Methods for quickPredict Objects |
llogisMLE | Maximum Likelihood Parameter Estimation of a Log Logistic Model with Possibly Censored Data |
lnormMLE | Maximum Likelihood Parameter Estimation of a Log Normal Model with Possibly Censored Data |
lockedTrain | Construct and Plot Time-Dependent Cross-correlation Diagram |
logLik.durationFit | Utility Functions for durationFit Objects |
maxIntensity | Simulate and Analyse Data From a Model Fitted With gss |
mkAR | Generate a Data Frame With Variables Suitable For an AR Like Model |
mkCPSP | Counting Process Sample Paths |
mkDummy | Generates a Data Frame of Dummy Variables for Use in gam |
mkGLMdf | Formats (lists of) spikeTrain and repeatedTrain Objects into Data Frame for use in glm, mgcv and gam |
mkM2U | Makes a Smooth Function Mapping a Data Frame Variable Onto a Variable Uniform on Its Definition Domain |
mkMappedI | Simulate and Analyse Data From a Model Fitted With gss |
mkPostSimAnalysis | Simulate and Analyse Data From a Model Fitted With gss |
mkREdf | Evaluates RateEvolutions for spikeTrain Lists and Returns Data Frame |
mkSelf | Simulate and Analyse Data From a Model Fitted With gss |
mkSimFct | Simulate and Analyse Data From a Model Fitted With gss |
mkTightBMtargetFct | Computations of Boundary Crossing Probabilities for the Wiener Process |
mPK | Spike Trains of a Purkinje Cells (PC) Recorded in Control Conditions and With Bath Applied Bicuculline |
persp.jpsth | Related Functions and Methods for Joint-PSTHs and Joint Scatter Diagrams |
persp.quickPredict | Graphical Methods for quickPredict Objects |
pinvgauss | The Inverse Gaussian Distribution |
pllogis | The Log Logistic Distribution |
plot.CountingProcessSamplePath | Counting Process Sample Paths |
plot.CountingProcessSamplePath.summary | Create and Explore Counting Process Sample Path Summaries |
plot.FirstPassageTime | Computations of Boundary Crossing Probabilities for the Wiener Process |
plot.frt | Plots and Summarizes frt Objects. |
plot.gamlockedTrain | Function to Smooth a lockedTrain Object and Related Methods: The Penalized Regression Spline Approach |
plot.gampsth | Smooth Peri Stimulus Time Histogram Related Functions and Methods: The Penalized Regression Spline Approach |
plot.gsslockedTrain | Function to Smooth a lockedTrain Object and Related Methods: The Smoothing Spline Approach |
plot.gsslockedTrain0 | Function to Smooth a lockedTrain Object and Related Methods: The Smoothing Spline Approach |
plot.gsspsth | Smooth Peri Stimulus Time Histogram Related Functions and Methods: The Smoothing Spline Approach |
plot.gsspsth0 | Smooth Peri Stimulus Time Histogram Related Functions and Methods: The Smoothing Spline Approach |
plot.hist.lockedTrain | Auto- and Cross-Intensity Function Estimate for Spike Trains |
plot.lockedTrain | Construct and Plot Time-Dependent Cross-correlation Diagram |
plot.psth | Compute and Plot Peri-Stimulus Time Histogram |
plot.quickPredict | Graphical Methods for quickPredict Objects |
plot.rateEvolution | Evaluates and Plots a Spike Train Firing Rate's Evolution |
plot.repeatedTrain | Generate a Raster Plot |
plot.spikeTrain | Display Counting Process Associated with Single Spike Train |
plot.ssanova | A Plot Method for ssanova and ssanvoa0 Objects Tailored to Their Use in STAR |
plot.ssanova0 | A Plot Method for ssanova and ssanvoa0 Objects Tailored to Their Use in STAR |
plot.transformedTrain | Plot Diagnostics for an transformedTrain Object |
plot.varianceTime | Variance-Time Analysis for Spike Trains |
predictLogProb | Compute the Log Probability of a "New" Data Set Using a Fitted Model Prediction |
prexp | The Refractory Exponential Distribution |
print.CountingProcessSamplePath | Counting Process Sample Paths |
print.CountingProcessSamplePath.summary | Create and Explore Counting Process Sample Path Summaries |
print.FirstPassageTime | Computations of Boundary Crossing Probabilities for the Wiener Process |
print.gamlockedTrain | Function to Smooth a lockedTrain Object and Related Methods: The Penalized Regression Spline Approach |
print.gampsth | Smooth Peri Stimulus Time Histogram Related Functions and Methods: The Penalized Regression Spline Approach |
print.gsslockedTrain | Function to Smooth a lockedTrain Object and Related Methods: The Smoothing Spline Approach |
print.gsslockedTrain0 | Function to Smooth a lockedTrain Object and Related Methods: The Smoothing Spline Approach |
print.gsspsth | Smooth Peri Stimulus Time Histogram Related Functions and Methods: The Smoothing Spline Approach |
print.gsspsth0 | Smooth Peri Stimulus Time Histogram Related Functions and Methods: The Smoothing Spline Approach |
print.lockedTrain | Construct and Plot Time-Dependent Cross-correlation Diagram |
print.repeatedTrain | Print and Summary Methods for repeatedTrain Objects |
print.spikeTrain | Print and Summary Methods for spikeTrain Objects |
print.summary.repeatedTrain | Print and Summary Methods for repeatedTrain Objects |
psth | Compute and Plot Peri-Stimulus Time Histogram |
qinvgauss | The Inverse Gaussian Distribution |
qllogis | The Log Logistic Distribution |
qqDuration | Quantile-Quantile Plot For Fitted Duration Distributions |
qrexp | The Refractory Exponential Distribution |
quickPredict | A Simple Interface to predict method for ssanova and ssanova0 objects |
raster | Generate a Raster Plot |
rateEvolution | Evaluates and Plots a Spike Train Firing Rate's Evolution |
renewalTestPlot | Non-Parametric Tests for Renewal Processes |
reportHTML | Generic Function for Automatic HTML Report Generation |
reportHTML.gam | Generates a Report in HTML Format from a STAR gam Object |
reportHTML.repeatedTrain | Performs Basic Spike Train Analysis and Generates a Report in HTML Format from a repeatedTrain Object |
reportHTML.spikeTrain | Performs Basic Spike Train Analysis and Generates a Report in HTML Format from a spikeTrain Object |
rexpMLE | Maximum Likelihood Parameter Estimation of a Refractory Exponential Model with Possibly Censored Data |
rinvgauss | The Inverse Gaussian Distribution |
rllogis | The Log Logistic Distribution |
rrexp | The Refractory Exponential Distribution |
ShallowShocks | Shallow Shocks (M >= 6.0) in OFF Tohoku Area for 1885-1980 |
simulate.gsspsth | Smooth Peri Stimulus Time Histogram Related Functions and Methods: The Smoothing Spline Approach |
simulate.gsspsth0 | Smooth Peri Stimulus Time Histogram Related Functions and Methods: The Smoothing Spline Approach |
sPK | Spike Trains of a Purkinje Cells (PC) Recorded in Control Conditions and With Bath Applied Bicuculline |
STAR | Spike Train Analysis with R |
summary.CountingProcessSamplePath | Create and Explore Counting Process Sample Path Summaries |
summary.FirstPassageTime | Computations of Boundary Crossing Probabilities for the Wiener Process |
summary.frt | Plots and Summarizes frt Objects. |
summary.gamlockedTrain | Function to Smooth a lockedTrain Object and Related Methods: The Penalized Regression Spline Approach |
summary.gampsth | Smooth Peri Stimulus Time Histogram Related Functions and Methods: The Penalized Regression Spline Approach |
summary.gsslockedTrain | Function to Smooth a lockedTrain Object and Related Methods: The Smoothing Spline Approach |
summary.gsslockedTrain0 | Function to Smooth a lockedTrain Object and Related Methods: The Smoothing Spline Approach |
summary.gsspsth | Smooth Peri Stimulus Time Histogram Related Functions and Methods: The Smoothing Spline Approach |
summary.gsspsth0 | Smooth Peri Stimulus Time Histogram Related Functions and Methods: The Smoothing Spline Approach |
summary.repeatedTrain | Print and Summary Methods for repeatedTrain Objects |
summary.spikeTrain | Print and Summary Methods for spikeTrain Objects |
summary.transformedTrain | Summary of transformedTrain Objects |
thinProcess | Simulate and Analyse Data From a Model Fitted With gss |
transformedTrain | Performs Time Transformation of Spike Trains Fitted with glm or gam |
varianceTime | Variance-Time Analysis for Spike Trains |
weibullMLE | Maximum Likelihood Parameter Estimation of a Weibull Model with Possibly Censored Data |
%frt% | Computes Forward Recurrence Times from Two transformedTrain Objects |
%qp% | A Simple Interface to predict method for ssanova and ssanova0 objects |
%tt% | Time Transformation Using a gssanova Objet |
[.spikeTrain | Coerce, Test and Extract from spikeTrain Objects |