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PyGeodesy
Package pygeodesy :: Module fstats :: Class Fcook
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Class Fcook

  object --+            
           |            
named._Named --+        
               |        
    _FstatsNamed --+    
                   |    
         _FstatsBase --+
                       |
                      Fcook

Cook's RunningStats computing the running mean, median and (sample) kurtosis, skewness, variance, standard deviation and Jarque-Bera normality.

See Also: Fwelford and Higher-order statistics.

Instance Methods
 
__init__(self, xs=None, **name)
New Fcook stats accumulator.
 
__iadd__(self, other)
Add other to this Fcook instance.
 
fadd(self, xs, sample=False)
Accumulate and return the current count.
 
fjb(self, xs=None, excess=True, sample=True)
Accumulate and compute the current Jarque-Bera normality.
 
fjb_(self, *xs, **sample_excess)
Accumulate and compute the current Jarque-Bera normality.
 
fkurtosis(self, xs=None, excess=True, **sample)
Accumulate and return the current kurtosis.
 
fkurtosis_(self, *xs, **excess_sample)
Accumulate and return the current kurtosis.
 
fmedian(self, xs=None)
Accumulate and return the current median.
 
fmedian_(self, *xs)
Accumulate and return the current median.
 
fskewness(self, xs=None, **sample)
Accumulate and return the current skewness.
 
fskewness_(self, *xs, **sample)
Accumulate and return the current skewness.
 
toFwelford(self, **name)
Return a Fwelford equivalent.

Inherited from _FstatsBase: fadd_, fmean, fmean_, fstdev, fstdev_, fvariance, fvariance_

Inherited from _FstatsNamed: __add__, __float__, __int__, __len__, __neg__, __radd__, __str__, copy, fcopy

Inherited from named._Named: __imatmul__, __matmul__, __repr__, __rmatmul__, attrs, classof, dup, methodname, rename, renamed, toRepr, toStr, toStr2

Inherited from object: __delattr__, __format__, __getattribute__, __hash__, __new__, __reduce__, __reduce_ex__, __setattr__, __sizeof__, __subclasshook__

Properties

Inherited from named._Named: classname, classnaming, iteration, name, named, named2, named3, named4, sizeof

Inherited from object: __class__

Method Details

__init__ (self, xs=None, **name)
(Constructor)

 

New Fcook stats accumulator.

Arguments:
  • xs - Iterable of additional values (each scalar, an Fsum or Fsum2Tuple).
  • name - Optional name=NN (str).
Overrides: object.__init__

See Also: Method Fcook.fadd.

__iadd__ (self, other)

 

Add other to this Fcook instance.

Arguments:
  • other - An Fcook instance or value or iterable of values (each scalar, an Fsum or Fsum2Tuple).
Returns:
This instance, updated (Fcook).
Raises:
  • TypeError - Invalid other.
  • ValueError - Invalid or non-finite other.

See Also: Method Fcook.fadd.

fadd (self, xs, sample=False)

 

Accumulate and return the current count.

Arguments:
  • xs - Iterable of additional values (each scalar, an Fsum or Fsum2Tuple).
  • sample - Use sample=True for the sample count instead of the population count (bool).
Returns:
Current, running (sample) count (int).
Raises:
  • OverflowError - Partial 2sum overflow.
  • TypeError - Invalid xs.
  • ValueError - Invalid or non-finite xs.
Overrides: _FstatsBase.fadd

See Also: online_kurtosis.

fjb (self, xs=None, excess=True, sample=True)

 

Accumulate and compute the current Jarque-Bera normality.

Arguments:
  • xs - Iterable of additional values (each scalar, an Fsum or Fsum2Tuple).
  • excess - Apply the excess kurtosis (bool), default.
  • sample - Use sample=False for the population normality instead of the sample one (bool).
Returns:
Current, running (sample) Jarque-Bera normality (float).

See Also: Method Fcook.fadd.

fjb_ (self, *xs, **sample_excess)

 

Accumulate and compute the current Jarque-Bera normality.

See Also: Method Fcook.fjb for further details.

fkurtosis (self, xs=None, excess=True, **sample)

 

Accumulate and return the current kurtosis.

Arguments:
  • xs - Iterable of additional values (each scalar, an Fsum or Fsum2Tuple).
  • excess - Return the excess kurtosis (bool), default.
  • sample - Use sample=True for the sample kurtosis instead of the population kurtosis (bool).
Returns:
Current, running (sample) kurtosis or excess kurtosis (float).
See Also:
Kurtosis Formula and Mantalos., Method Fcook.fadd.

fkurtosis_ (self, *xs, **excess_sample)

 

Accumulate and return the current kurtosis.

See Also: Method Fcook.fkurtosis for further details.

fmedian (self, xs=None)

 

Accumulate and return the current median.

Arguments:
  • xs - Iterable of additional values (each scalar, an Fsum or Fsum2Tuple).
Returns:
Current, running median (float).

See Also: Pearson's Skewness Coefficients, Skewness & Kurtosis Simplified https://TowardsDataScience.com/skewness-kurtosis-simplified-1338e094fc85> and method Fcook.fadd.

fmedian_ (self, *xs)

 

Accumulate and return the current median.

See Also: Method Fcook.fmedian for further details.

fskewness (self, xs=None, **sample)

 

Accumulate and return the current skewness.

Arguments:
  • xs - Iterable of additional values (each scalar, an Fsum or Fsum2Tuple).
  • sample - Use sample=True for the sample skewness instead of the population skewness (bool).
Returns:
Current, running (sample) skewness (float).
See Also:
Skewness Formula and Mantalos., Method Fcook.fadd.

fskewness_ (self, *xs, **sample)

 

Accumulate and return the current skewness.

See Also: Method Fcook.fskewness for further details.

toFwelford (self, **name)

 

Return a Fwelford equivalent.

Arguments:
  • name - Optional name=NN (str).

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