globalfit-class {DistributionFitR} | R Documentation |

The class `globalfit`

handles return objects
from globalfit. It contains for some given data a list of fitted
distributions, their estimated parameters and supplementary information.

Objects can be created by calls of the form
`new("globalfit", data, continuity, method, fits)`

.
More comfortably, you may use the function `globalfit`

.
The result of these calls is a globalfit object.

- call
the call, which created this object

- data
vector of data points

- continuity
logical; if

`TRUE`

, indicating that the data points come from a continuous distribution; if`FALSE`

, indicating that they come from a discrete distribution- method
character; the method used for the fit.

- fits
list of S4-objects of class

`optimParams`

- summary
`signature(object = "globalfit")`

: summarizes the object and creates an object of`globalfitSummary`

. Specify argument`ic`

to choose how the results are to be sorted (as in method`sort`

.- hist
`signature(x = "globalfit")`

: computes a histogram of the given data points and plots it together with the density of the estimated best fit. Specify argument`which`

to choose which fitted density to overlay: the number of the fit as returned by`summary`

; i.e.`which = 1`

for the best fit,`which = 2`

for the second-best etc.

Default is`1`

.`signature(x = "globalfit")`

: applies the method`summary`

and prints the result.

- AIC
`signature(x = "globalfit")`

: shows the AIC value of the fits. Specify argument`n`

to display AIC for the`n`

best fits according to this criterion.- BIC
`signature(x = "globalfit")`

: shows the BIC value of the fits. Specify argument`n`

to display BIC for the`n`

best fits according to this criterion.

- sort
`signature(x = "globalfit")`

: sorts the results in slot`fits`

by the information criterium selected. in argument`ic`

. Available options are`"AIC"`

,`"BIC"`

or`"AICc"`

.

Moritz Lauff, Kiril Dik, Nadine Tampe, Borui Niklas Zhu, Benedikt Geier, Moritz Kern

`globalfitSummary`

`optimParams`

`globalfit`

```
data <- rnorm(n = 100, mean = 10, sd = 1)
r <- globalfit(data, cores = if(interactive()) NULL else 2)
sort(r, ic = 'BIC')
print(r)
summary(r)
summary(r, ic = 'AICc', n = 7)
hist(r, ic = 'BIC', which = 4)
AIC(r, n = 2)
BIC(r)
```

[Package *DistributionFitR* version 0.1 Index]