Column-wise MLE of the angular Gaussian and the von Mises Fisher distributions | R Documentation |

Column-wise MLE of the angular Gaussian and the von Mises Fisher distributions.

```
colspml.mle(x ,tol = 1e-07, maxiters = 100, parallel = FALSE)
colvm.mle(x, tol = 1e-07)
```

`x` |
A numerical matrix with data. Each column refers to a different vector of observations of the same distribution. The values of for Lognormal must be greater than zero, for the logitnormal they must by percentages, exluding 0 and 1, whereas for the Borel distribution the x must contain integer values greater than 1. |

`tol` |
The tolerance value to terminate the Newton-Raphson algorithm. |

`maxiters` |
The maximum number of iterations that can take place in each regression. |

`parallel` |
Do you want this to be executed in parallel or not. The parallel takes place in C++, and the number of threads is defined by each system's availiable cores. |

For each column, spml.mle function is applied that fits the angular Gaussian distribution estimates its parameters and computes the maximum log-likelihood.

A matrix with four columns. The first two are the mean vector, then the `\gamma`

parameter, and the fourth
column contains maximum log-likelihood.

Michail Tsagris.

R implementation and documentation: Michail Tsagris mtsagris@uoc.gr.

Presnell Brett, Morrison Scott P. and Littell Ramon C. (1998). Projected multivariate linear models for directional data. Journal of the American Statistical Association, 93(443): 1068–1077.

```
spml.mle, spml.reg, vm.mle, vmf.mle
```

```
x <- matrix( runif(100 * 10), ncol = 10)
a <- colspml.mle(x)
b <- colvm.mle(x)
x <- NULL
```

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