A link joins two univariate statistics as a sequence.

This can be used to pipe the output of one statistic to the input of another. This can be used, for instance, to calculate the mean of the variance of a variable. It can also be used to compute shifted statistics by piping statistics with an instance of stats.Shift.

Note that a link is not meant to be instantiated via this class definition. Instead, users can link statistics together via the | operator.

## Parameters¶

• left (river.stats.base.Univariate)

• right (river.stats.base.Univariate)

The output from left's get method is passed to right's update method if left's get method doesn't produce None.

• name

## Examples¶

>>> from river import stats
>>> stat = stats.Shift(1) | stats.Mean()


No values have been seen, therefore get defaults to the initial value of stats.Mean, which is 0.

>>> stat.get()
0.


Let us now call update.

>>> stat = stat.update(1)


The output from get will still be 0. The reason is that stats.Shift has not enough values, and therefore outputs it's default value, which is None. The stats.Mean instance is therefore not updated.

>>> stat.get()
0.0


On the next call to update, the stats.Shift instance has seen enough values, and therefore the mean can be updated. The mean is therefore equal to 1, because that's the only value from the past.

>>> stat = stat.update(3)
>>> stat.get()
1.0


On the subsequent call to update, the mean will be updated with the value 3.

>>> stat = stat.update(4)
>>> stat.get()
2.0


Note that composing statistics returns a new statistic with it's own name.

>>> stat.name
'mean_of_shift_1'


## Methods¶

clone

Return a fresh estimator with the same parameters.

The clone has the same parameters but has not been updated with any data. This works by looking at the parameters from the class signature. Each parameter is either - recursively cloned if it's a River classes. - deep-copied via copy.deepcopy if not. If the calling object is stochastic (i.e. it accepts a seed parameter) and has not been seeded, then the clone will not be idempotent. Indeed, this method's purpose if simply to return a new instance with the same input parameters.

get

Return the current value of the statistic.

revert

Revert and return the called instance.

Parameters

• x
update

Update and return the called instance.

Parameters

• x