combdist.mle {distributionsrd} | R Documentation |

## Combined distributions MLE

### Description

Maximum Likelihood estimation for combined ( single, composite and finite mixture) truncated or complete distributions.

### Usage

```
combdist.mle(
x,
dist,
start = NULL,
lower = NULL,
upper = NULL,
components = 1,
nested = FALSE,
steps = 1,
lowertrunc = 0,
uppertrunc = Inf,
...
)
```

### Arguments

`x` |
data vector |

`dist` |
character vector denoting the distribution(s). |

`start` |
named numeric vector holding the starting values for the coefficients. |

`lower` , `upper` |
Lower and upper bounds to the estimated coefficients, defaults to -Inf and Inf respectively. |

`components` |
number of components for a mixture distribution. |

`nested` |
logical indicating whether results should be returned in a nested list or a flat list form, defaults to FALSE. |

`steps` |
number of steps taken in stepflexmix, defaults to 1. |

`lowertrunc` , `uppertrunc` |
lowertrunc- and uppertrunc truncation points, defaults to 0 and Inf respectively |

`...` |
Additional arguments. |

### Value

Returns a named list containing a

- dist
Character vector denoting the distributions, separated by an underscore

- components
Nr. of combined distributions

- prior
Weights assigned to the respective component distributions

- coefficients
Named vector of coefficients

- convergence
logical indicator of convergence

- n
Length of the fitted data vector

- np
Nr. of coefficients

### Examples

```
x <- rdoubleparetolognormal(1e3)
combdist.mle(x = x, dist = "doubleparetolognormal") # Double-Pareto Lognormal
combdist.mle(x = x, components = 2, dist = "lnorm", steps = 20) # FMM with 2 components
combdist.mle( x = x, dist = c("invpareto", "lnorm", "pareto"),
start = c(coeff1.k = 1, coeff2.meanlog = mean(log(x)), coeff2.sdlog = sd(log(x)), coeff3.k = 1),
lower = c(1e-10, -Inf, 1e-10, 1e-10), upper = c(Inf, Inf, Inf, Inf), nested = TRUE)
# composite distribution
```

*distributionsrd*version 0.0.6 Index]