Spike Train Analysis with R
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Documentation for package ‘STAR’ version 0.3-7
- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Code demos. Use demo() to run them.
Help Pages
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 |
-- A --
| 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 |
-- B --
| brt4df | Get Backward Recurrence Times from Data Frames Generated by mkGLMdf |
-- C --
| 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 |
-- D --
| 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 |
-- E --
| 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 |
-- F --
| frt | Computes Forward Recurrence Times from Two transformedTrain Objects |
-- G --
| 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 |
-- H --
| 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 |
-- I --
| 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 |
-- J --
| 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 |
-- L --
| 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 |
-- M --
| 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 |
-- P --
| 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 |
-- Q --
| 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 |
-- R --
| 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 |
-- S --
| 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 |
-- T --
| thinProcess | Simulate and Analyse Data From a Model Fitted With gss |
| transformedTrain | Performs Time Transformation of Spike Trains Fitted with glm or gam |
-- V --
| varianceTime | Variance-Time Analysis for Spike Trains |
-- W --
| weibullMLE | Maximum Likelihood Parameter Estimation of a Weibull Model with Possibly Censored Data |
-- misc --
| %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 |