B C D E G I K L M O P R S T V W misc
| tigre-package | tigre - Transcription factor Inference through Gaussian process Reconstruction of Expression |
| baseloglikelihoods | Class "scoreList" |
| baseloglikelihoods-method | Class "scoreList" |
| baseloglikelihoods<- | Class "scoreList" |
| baseloglikelihoods<--method | Class "scoreList" |
| boundedTransform | Constrains a parameter. |
| c-method | Class "scoreList" |
| CGoptim | Optimise the given function using (scaled) conjugate gradients. |
| cgpdisimExpandParam | Update a model structure with new parameters or update the posterior processes. |
| cgpdisimExtractParam | Extract the parameters of a model. |
| cgpdisimGradient | Model log-likelihood/objective error function and its gradient. |
| cgpdisimLogLikeGradients | Model log-likelihood/objective error function and its gradient. |
| cgpdisimLogLikelihood | Model log-likelihood/objective error function and its gradient. |
| cgpdisimObjective | Model log-likelihood/objective error function and its gradient. |
| cgpdisimUpdateProcesses | Update a model structure with new parameters or update the posterior processes. |
| cgpsimExpandParam | Update a model structure with new parameters or update the posterior processes. |
| cgpsimExtractParam | Extract the parameters of a model. |
| cgpsimGradient | Model log-likelihood/objective error function and its gradient. |
| cgpsimLogLikeGradients | Model log-likelihood/objective error function and its gradient. |
| cgpsimLogLikelihood | Model log-likelihood/objective error function and its gradient. |
| cgpsimObjective | Model log-likelihood/objective error function and its gradient. |
| cgpsimOptimise | Optimise the given function using (scaled) conjugate gradients. |
| cgpsimUpdateProcesses | Update a model structure with new parameters or update the posterior processes. |
| cmpndKernCompute | Compute the kernel given the parameters and X. |
| cmpndKernDiagCompute | Compute the kernel given the parameters and X. |
| cmpndKernDiagGradX | Compute the gradient of the kernel wrt X. |
| cmpndKernDisplay | Display a model. |
| cmpndKernExpandParam | Update a model structure with new parameters or update the posterior processes. |
| cmpndKernExtractParam | Extract the parameters of a model. |
| cmpndKernGradient | Compute the gradient wrt the kernel parameters. |
| cmpndKernGradX | Compute the gradient of the kernel wrt X. |
| cmpndKernParamInit | Initialise a kernel structure. |
| datasetName | Class "scoreList" |
| datasetName-method | Class "scoreList" |
| datasetName<- | Class "scoreList" |
| datasetName<--method | Class "scoreList" |
| disimKernCompute | Compute the kernel given the parameters and X. |
| disimKernDiagCompute | Compute the kernel given the parameters and X. |
| disimKernDisplay | Display a model. |
| disimKernExpandParam | Update a model structure with new parameters or update the posterior processes. |
| disimKernExtractParam | Extract the parameters of a model. |
| disimKernGradient | Compute the gradient wrt the kernel parameters. |
| disimKernParamInit | Initialise a kernel structure. |
| disimXdisimKernCompute | Compute the kernel given the parameters and X. |
| disimXdisimKernGradient | Compute the gradient wrt the kernel parameters. |
| disimXrbfKernCompute | Compute the kernel given the parameters and X. |
| disimXrbfKernGradient | Compute the gradient wrt the kernel parameters. |
| disimXsimKernCompute | Compute the kernel given the parameters and X. |
| disimXsimKernGradient | Compute the gradient wrt the kernel parameters. |
| drosophila_gpsim_fragment | Fragment of 12 time point Drosophila embryonic development microarray gene expression time series |
| drosophila_mmgmos_fragment | Fragment of 12 time point Drosophila embryonic development microarray gene expression time series |
| experimentSet | Class "scoreList" |
| experimentSet-method | Class "scoreList" |
| experimentSet<- | Class "scoreList" |
| experimentSet<--method | Class "scoreList" |
| export.scores | Export results to an SQLite database |
| ExpressionTimeSeries | Class to contain time series expression assays |
| ExpressionTimeSeries-class | Class to contain time series expression assays |
| expTransform | Constrains a parameter. |
| gammaPriorExpandParam | Update a model structure with new parameters or update the posterior processes. |
| gammaPriorExtractParam | Extract the parameters of a model. |
| gammaPriorGradient | Model log-likelihood/objective error function and its gradient. |
| gammaPriorLogProb | Model log-likelihood/objective error function and its gradient. |
| gammaPriorParamInit | Initialise a kernel structure. |
| generateModels | Generating models with the given data |
| genes | Class "scoreList" |
| genes-method | Class "scoreList" |
| genes<- | Class "scoreList" |
| genes<--method | Class "scoreList" |
| gpdisimCreate | Create a GPSIM/GPDISIM model. |
| gpdisimDisplay | Display a model. |
| gpdisimExpandParam | Update a model structure with new parameters or update the posterior processes. |
| gpdisimExtractParam | Extract the parameters of a model. |
| gpdisimGradient | Model log-likelihood/objective error function and its gradient. |
| gpdisimLogLikeGradients | Model log-likelihood/objective error function and its gradient. |
| gpdisimLogLikelihood | Model log-likelihood/objective error function and its gradient. |
| gpdisimObjective | Model log-likelihood/objective error function and its gradient. |
| gpdisimUpdateProcesses | Update a model structure with new parameters or update the posterior processes. |
| GPLearn | Fit a GP model |
| GPModel | A container for gpsim models |
| GPModel-class | A container for gpsim models |
| GPPlot | Plot GP(DI)SIM models |
| GPRankTargets | Ranking possible target genes or regulators |
| GPRankTFs | Ranking possible target genes or regulators |
| gpsimCreate | Create a GPSIM/GPDISIM model. |
| gpsimDisplay | Display a model. |
| gpsimExpandParam | Update a model structure with new parameters or update the posterior processes. |
| gpsimExtractParam | Extract the parameters of a model. |
| gpsimGradient | Model log-likelihood/objective error function and its gradient. |
| gpsimLogLikeGradients | Model log-likelihood/objective error function and its gradient. |
| gpsimLogLikelihood | Model log-likelihood/objective error function and its gradient. |
| gpsimObjective | Model log-likelihood/objective error function and its gradient. |
| gpsimUpdateProcesses | Update a model structure with new parameters or update the posterior processes. |
| initialize-method | Class to contain time series expression assays |
| initialize-method | A container for gpsim models |
| invgammaPriorExpandParam | Update a model structure with new parameters or update the posterior processes. |
| invgammaPriorExtractParam | Extract the parameters of a model. |
| invgammaPriorGradient | Model log-likelihood/objective error function and its gradient. |
| invgammaPriorLogProb | Model log-likelihood/objective error function and its gradient. |
| invgammaPriorParamInit | Initialise a kernel structure. |
| is.GPModel | A container for gpsim models |
| is.GPModel-method | A container for gpsim models |
| kernCompute | Compute the kernel given the parameters and X. |
| kernCreate | Initialise a kernel structure. |
| kernDiagCompute | Compute the kernel given the parameters and X. |
| kernDiagGradX | Compute the gradient of the kernel wrt X. |
| kernDisplay | Display a model. |
| kernExpandParam | Update a model structure with new parameters or update the posterior processes. |
| kernExtractParam | Extract the parameters of a model. |
| kernGradient | Compute the gradient wrt the kernel parameters. |
| kernGradX | Compute the gradient of the kernel wrt X. |
| kernParamInit | Initialise a kernel structure. |
| kernPriorGradient | Model log-likelihood/objective error function and its gradient. |
| kernPriorLogProb | Model log-likelihood/objective error function and its gradient. |
| knownTargets | Class "scoreList" |
| knownTargets-method | Class "scoreList" |
| knownTargets<- | Class "scoreList" |
| knownTargets<--method | Class "scoreList" |
| length-method | Class "scoreList" |
| lnDiffErfs | Helper function for computing the log of difference |
| loglikelihoods | Class "scoreList" |
| loglikelihoods-method | Class "scoreList" |
| loglikelihoods<- | Class "scoreList" |
| loglikelihoods<--method | Class "scoreList" |
| mlpKernCompute | Compute the kernel given the parameters and X. |
| mlpKernDiagGradX | Compute the gradient of the kernel wrt X. |
| mlpKernExpandParam | Update a model structure with new parameters or update the posterior processes. |
| mlpKernExtractParam | Extract the parameters of a model. |
| mlpKernGradient | Compute the gradient wrt the kernel parameters. |
| mlpKernGradX | Compute the gradient of the kernel wrt X. |
| mlpKernParamInit | Initialise a kernel structure. |
| modelArgs | Class "scoreList" |
| modelArgs-method | Class "scoreList" |
| modelArgs<- | Class "scoreList" |
| modelArgs<--method | Class "scoreList" |
| modelDisplay | Display a model. |
| modelExpandParam | Update a model structure with new parameters or update the posterior processes. |
| modelExtractParam | Extract the parameters of a model. |
| modelGradient | Model log-likelihood/objective error function and its gradient. |
| modelLogLikelihood | Model log-likelihood/objective error function and its gradient. |
| modelObjective | Model log-likelihood/objective error function and its gradient. |
| modelOptimise | Optimise the given function using (scaled) conjugate gradients. |
| modelStruct | A container for gpsim models |
| modelStruct-method | A container for gpsim models |
| modelStruct<- | A container for gpsim models |
| modelStruct<--method | A container for gpsim models |
| modelTieParam | Tie parameters of a model together. |
| modelType | A container for gpsim models |
| modelType-method | A container for gpsim models |
| modelUpdateProcesses | Update a model structure with new parameters or update the posterior processes. |
| multiKernCompute | Compute the kernel given the parameters and X. |
| multiKernDiagCompute | Compute the kernel given the parameters and X. |
| multiKernDisplay | Display a model. |
| multiKernExpandParam | Update a model structure with new parameters or update the posterior processes. |
| multiKernExtractParam | Extract the parameters of a model. |
| multiKernGradient | Compute the gradient wrt the kernel parameters. |
| multiKernParamInit | Initialise a kernel structure. |
| optimiDefaultConstraint | Returns function for parameter constraint. |
| optimiDefaultOptions | Optimise the given function using (scaled) conjugate gradients. |
| params | Class "scoreList" |
| params-method | Class "scoreList" |
| params<- | Class "scoreList" |
| params<--method | Class "scoreList" |
| plotTimeseries | Plot ExpressionTimeSeries data |
| priorCreate | Initialise a kernel structure. |
| priorExpandParam | Update a model structure with new parameters or update the posterior processes. |
| priorExtractParam | Extract the parameters of a model. |
| priorGradient | Model log-likelihood/objective error function and its gradient. |
| priorLogProb | Model log-likelihood/objective error function and its gradient. |
| priorParamInit | Initialise a kernel structure. |
| processData | Processing expression time series |
| processRawData | Processing expression time series |
| rbfKernCompute | Compute the kernel given the parameters and X. |
| rbfKernDiagCompute | Compute the kernel given the parameters and X. |
| rbfKernDisplay | Display a model. |
| rbfKernExpandParam | Update a model structure with new parameters or update the posterior processes. |
| rbfKernExtractParam | Extract the parameters of a model. |
| rbfKernGradient | Compute the gradient wrt the kernel parameters. |
| rbfKernParamInit | Initialise a kernel structure. |
| SCGoptim | Optimise the given function using (scaled) conjugate gradients. |
| scoreList | Class "scoreList" |
| scoreList-class | Class "scoreList" |
| sharedModel | Class "scoreList" |
| sharedModel-method | Class "scoreList" |
| sharedModel<- | Class "scoreList" |
| sharedModel<--method | Class "scoreList" |
| show-method | A container for gpsim models |
| show-method | Class "scoreList" |
| sigmoidTransform | Constrains a parameter. |
| simKernCompute | Compute the kernel given the parameters and X. |
| simKernDiagCompute | Compute the kernel given the parameters and X. |
| simKernDisplay | Display a model. |
| simKernExpandParam | Update a model structure with new parameters or update the posterior processes. |
| simKernExtractParam | Extract the parameters of a model. |
| simKernGradient | Compute the gradient wrt the kernel parameters. |
| simKernParamInit | Initialise a kernel structure. |
| simXrbfKernCompute | Compute the kernel given the parameters and X. |
| simXrbfKernGradient | Compute the gradient wrt the kernel parameters. |
| simXsimKernCompute | Compute the kernel given the parameters and X. |
| simXsimKernGradient | Compute the gradient wrt the kernel parameters. |
| sort-method | Class "scoreList" |
| TF | Class "scoreList" |
| TF-method | Class "scoreList" |
| TF<- | Class "scoreList" |
| TF<--method | Class "scoreList" |
| tigre | tigre - Transcription factor Inference through Gaussian process Reconstruction of Expression |
| translateKernCompute | Compute the kernel given the parameters and X. |
| translateKernDiagCompute | Compute the kernel given the parameters and X. |
| translateKernExpandParam | Update a model structure with new parameters or update the posterior processes. |
| translateKernExtractParam | Extract the parameters of a model. |
| translateKernGradient | Compute the gradient wrt the kernel parameters. |
| translateKernParamInit | Initialise a kernel structure. |
| var.exprs | Class to contain time series expression assays |
| var.exprs-method | Class to contain time series expression assays |
| var.exprs<- | Class to contain time series expression assays |
| var.exprs<--method | Class to contain time series expression assays |
| whiteKernCompute | Compute the kernel given the parameters and X. |
| whiteKernDiagCompute | Compute the kernel given the parameters and X. |
| whiteKernDisplay | Display a model. |
| whiteKernExpandParam | Update a model structure with new parameters or update the posterior processes. |
| whiteKernExtractParam | Extract the parameters of a model. |
| whiteKernGradient | Compute the gradient wrt the kernel parameters. |
| whiteKernParamInit | Initialise a kernel structure. |
| whiteXwhiteKernCompute | Compute the kernel given the parameters and X. |
| whiteXwhiteKernGradient | Compute the gradient wrt the kernel parameters. |
| write.scores | Class "scoreList" |
| write.scores-method | Class "scoreList" |
| [-method | Class "scoreList" |