View source: R/DroppingInterval.R

summary.intRvals | R Documentation |

`intRvals`

summary method for class `intRvals`

## S3 method for class 'intRvals' summary(object, ...)

`object` |
An object of class |

`...` |
further arguments passed to or from other methods. |

The function `summary.intRvals`

computes and returns a list of summary statistics

`data`

the interval data

`mu`

the modelled mean interval

`mu.se`

the modelled mean interval standard error

`sigma`

the modelled interval standard deviation

`p`

the modelled probability to not observe an arrival

`fpp`

the modelled fraction of arrivals following a random poisson process, see intervalpdf

`N`

the highest number of consecutive missed arrivals taken into account, see intervalpdf

`convergence`

convergence field of optim

`counts`

counts field of optim

`loglik`

vector of length 2, with first element the log-likelihood of the fitted model, and second element the log-likelihood of the model without a missed event probability (i.e.

`p`

=0)`df.residual`

degrees of freedom, a 2-vector (1, number of intervals -

`n.param`

)`n.param`

number of optimized model parameters

`distribution`

assumed interval distribution, one of 'gamma' or 'normal'

`trunc`

interval range over which the interval pdf was truncated and normalized

`fpp.method`

A string equal to 'fixed' or 'auto'. When 'auto' fpp has been optimized as a free model parameter. When 'fixed' the model is fitted with a fixed value set by parameter

`fpp`

`deviance`

deviance between the fitted model and a model without a missed event probability (i.e.

`p`

=0)`p.value`

numeric vector with two elements. First element contains the p.value for a likelihood ratio (deviance) test between the fitted model and a model without a missed event probability (i.e.

`p`

=0). Second element contains the p.value for a likelihood ratio (deviance) test between the fitted model and a saturated null model.

data(goosedrop) dr=estinterval(goosedrop$interval) summary(dr)

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