The class `estimate.vpin`

is a blueprint for `S4`

objects
that store the results of the `VPIN`

estimation method using the function
`vpin()`

.

The function show() displays a description of the
estimate.vpin object: descriptive statistics of the `VPIN`

variable,
the set of relevant parameters, and the running time.

## Slots

`success`

(

`logical`

) returns the value`TRUE`

when the estimation has succeeded,`FALSE`

otherwise.`errorMessage`

(

`character`

) returns an error message if the`VPIN`

estimation has failed, and is empty otherwise.`parameters`

(

`numeric`

) returns a numeric vector of estimation parameters (tbSize, buckets, samplength, VBS, #days), where`tbSize`

is the size of timebars (in seconds);`buckets`

is the number of buckets per average volume day;`VBS`

is Volume Bucket Size (daily average volume/number of buckets`buckets`

);`samplength`

is the length of the window used to estimate`VPIN`

; and`#days`

is the number of days in the dataset.`bucketdata`

(

`dataframe`

) returns the dataframe containing detailed information about buckets. Following the output of Abad and Yague (2012) , we report for each bucket its identifier (`bucket`

), the aggregate buy volume (`agg.bVol`

), the aggregate sell volume (`agg.sVol`

), the absolute order imbalance (`AOI=|agg.bVol-agg.sVol|`

), the start time (`starttime`

), the end time (`endtime`

), the duration in seconds (`duration`

) as well as the`VPIN`

vector.`vpin`

(

`numeric`

) returns the vector of the volume-synchronized probabilities of informed trading.`dailyvpin`

(

`dataframe`

) returns the daily`VPIN`

values. Two variants are provided for any given day:`dvpin`

corresponds to the unweighted average of vpin values, and`dvpin.weighted`

corresponds to the average of vpin values weighted by bucket duration.`runningtime`

(

`numeric`

) returns the running time of the`VPIN`

estimation in seconds.