MixfMRI v0.1-0
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Mixture fMRI Clustering Analysis
Utilizing model-based clustering (unsupervised)
for functional magnetic resonance imaging (fMRI) data.
The developed methods (Chen and Maitra (2018, manuscript)) include
2D and 3D clustering analyses (for p-values with voxel locations) and
segmentation analyses (for p-values alone) for fMRI data where p-values
indicate significant level of activation responding to stimulate
of interesting. The analyses are mainly identifying active
voxel/signal associated with normal brain behaviors.
Analysis pipelines (R scripts) utilizing this package
(see examples in 'inst/workflow/') is also implemented with high
performance techniques.
Functions in MixfMRI
| Name | Description | |
| LRT | Likelihood ratio tests | |
| Simulations | Generate datasets for MixfMRI simulations | |
| Print Objects | Print fclust related outputs | |
| algorithm | Main algorithms implemented in fclust | |
| Plotting | Main plotting function | |
| Main functions | Main MixfMRI function | |
| MixfMRI Control | Sets of controls in MixfMRI | |
| Example Datasets | Example datasets in MixfMRI | |
| MixfMRI-package | fMRI Clustering Analysis | |
| initial | Main initialization functions | |
| Likelihood Mixture Tests with Identity Cov Matrix or Only p-values | Likelihood Mixture Tests with Identity Cov Matrix or Only p-values | |
| Density function of p-values | Density function of p-values | |
| False Discovery Rates for Spatial Signals | False Discovery Rates for Spatial Signals using Benjamini and Heller (2007) | |
| Generalized Cluster-Based Analysis (CBA) Method | Generalized Cluster-Based Analysis (CBA) Method | |
| Covariance Matrices | Covariance Matrices | |
| Compute Q values | Q-values using Benjamini and Hochberg (1995) | |
| Summarized Overlap | Summarized Overlap | |
| Covariance Matrices of Logit ETA | Covariance Matrices of Logit ETA | |
| Compute Statistics for Log Odds Ratio of Posterior Probability | Compute Statistics for Log Odds Ratio of Posterior Probability | |
| General Internal Functions | All General Internal Functions and Datasets | |
| Smoothing | Generate datasets with smoothing for MixfMRI simulations | |
| No Results! | ||
Vignettes of MixfMRI
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Details
| Date | 2018-04-25 |
| LazyLoad | yes |
| LazyData | yes |
| License | Mozilla Public License 2.0 |
| BugReports | https://github.com/snoweye/MixfMRI/issues |
| URL | https://github.com/snoweye/MixfMRI |
| NeedsCompilation | yes |
| Packaged | 2018-04-26 00:32:11 UTC; snoweye |
| Repository | CRAN |
| Date/Publication | 2018-04-26 11:38:14 UTC |
| enhances | AnalyzeFMRI , oro.nifti , pbdMPI (>= 0.3-4) |
| imports | EMCluster , fftw , MASS , Matrix , MixSim , RColorBrewer |
| depends | R (>= 3.4.0) |
| Contributors | Ranjan Maitra, Dan Nettleton |
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