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| Directional-package | This is an R package that provides methods for statistical analysis of Directional data. |
| acg | MLE of the angular central Gaussian distribution |
| Arotation | Rotation axis and angle of rotation given a rotation matrix. |
| bic.mixvmf | BIC to choose the number of components in a model based clustering using mixtures of von Mises-Fisher distributions |
| circ.cor1 | Correlation for circular variables using the cosinus and sinus formula of Jammaladaka and SenGupta (1988). |
| circ.cor2 | Correlation for circular variables using the cosinus and sinus formula of Mardia and Jupp (2000). |
| circ.summary | Summary statistics for circular data. |
| circlin.cor | Circular-linear correlation. |
| conc.test | A test for testing the equality of the concentration parameter among g samples, where g >= 2 for ciruclar data. |
| dirknn | k-NN algorithm using the arc cosinus distance. |
| dirknn.tune | k-NN algorithm using the arc cosinus distance. Tuning the k neigbours. |
| embed.aov | Analysis of variance for (hyper-)spherical data using the embedding approach. |
| embed.circaov | Analysis of variance for circular data using the embedding approach. |
| euclid | Euclidean transformation. |
| euclid.inv | Inverse of the Euclidean transformation. |
| f.rbing | Simulating from a Bingham distribution |
| fb.saddle | Saddlepoint approximations of the Fisher-Bingham distributions |
| fishkent | Hypothesis test for von Mises-Fisher distribution over Kent's distribution. |
| hcf.aov | Analysis of variance for (hyper-)spherical data using the high concentration F test. |
| hcf.circaov | Analysis of variance for circular data using the high concentration F test. |
| het.aov | Analysis of variance for (hyper-)spherical data without assuming equality of the concentration parameters. |
| het.circaov | Analysis of variance for circular data without assuming equal concentration parameters. |
| kent.contour | Contour plot of the Kent distribution without any data. |
| kent.datacontour | Contour plot of the Kent distribution without any data. |
| kent.mle | MLe of the Kent distribution. |
| lambert | Lambert's equal area projection |
| lambert.inv | Inverse of Lambert's equal area projection |
| lr.aov | Analysis of variance for (hyper-)spherical data using the log-likelihood ratio test. |
| lr.circaov | Analysis of variance for circular data using the log-likelihood ratio test. |
| meandir.test | Test for a given mean direction. |
| mediandir | Spherical and hyperspherical median. |
| mediandir_2 | Fast calculation of the spherical and hyperspherical median. |
| mix.vmf | Mixtures of Von Mises-Fisher distributions. |
| mixvmf.contour | Contour plot of a mixture of von Mises-Fisher distributions model for spherical data only. |
| rayleigh | Rayleigh's test of uniformity. |
| rbingham | Simulation from a Bingham distribution using any symmetric matrix A |
| rfb | Simulation of random values from a Fisher-Bingham distribution |
| rmixvmf | Random values simulation from a mixture of von Mises-Fisher distributions. |
| rot.matrix | Rotation matrix from a rotation axis and angle of rotation. |
| rotation | Rotation matrix to rotate a spherical vector along the direction of another. |
| rvmf | Random values simulation from a von Mises-Fisher distribution. |
| rvonmises | Random values simulation from a von Mises-Fisher distribution. |
| spher.cor | Spherical-spherical correlation. |
| spher.reg | Spherical-Spherical regression. |
| spherconc.test | Test for equality of concentration parameters for spherical data |
| spml.reg | Circular or angular regression. |
| tang.conc | A test for testing the equality of the concentration parameter among g samples, where g >= 2 for ciruclar data. |
| vm.kde | Kernel density estimation of circular data with a von Mises kernel. |
| vmf | MLe of the parameters of a von Mises-Fisher distribution. |
| vmf.contour | Contour plots of the von Mises-Fisher distribution on the sphere. |
| vmf.da | Cross validation for estimating the classification rate of a discrminant analysis for directional data assuming a von Mises-Fisher distribution. |
| vmf.kde | Kernel density estimation for (hyper-)spherical data using a von Mises-Fisher kernel. |
| vmf.kerncontour | Contour plot of spherical data using a von Mises-Fisher kernel density estimate. |
| vmfda.pred | Prediction of a new observation using discriminant analysis based on von Mises-Fisher distributions. |
| vmfkde.tune | Tuning of the bandwidth parameter in the von Mises-Fisher kernel for (hyper-)spherical data. |
| vmfkde.tune_2 | Fast tuning of the bandwidth parameter in the von Mises-Fisher kernel for (hyper-)spherical data with an optimizer. |
| vmkde.tune | Tuning of the bandwidth parameter in the von Mises kernel for circular data. |
| vmkde.tune_2 | Fast tuning of the bandwidth parameter in the von Mises kernel for circular data. |
| wood.mle | MLe of the Wood bimodal distribution on the sphere. |