get_weighted_variance()

get_weighted_variance() computes the weighted variance of a numeric vector.

Function Usage

from sequenzo import get_weighted_variance
value = get_weighted_variance(values, weights=None, remove_missing=True, method="unbiased")

Entry Parameters

Parameter	Required	Type	Description
values	✓	array-like	Numeric values to summarize.
weights	✗	array-like or None	Optional weights. If None, all values are equally weighted.
remove_missing	✗	bool	If True, remove missing values before computing.
method	✗	str	Variance estimation method, default unbiased.

What It Does

• Validates inputs and aligns values and weights.
• Optionally removes missing values.
• Computes weighted variance using the selected method.

Returns

float.

Examples

from sequenzo import get_weighted_variance

values = [2, 4, 8]
weights = [1, 1, 2]

result = get_weighted_variance(values, weights=weights, method="unbiased")
print(result)

R Counterpart

• Closest R counterpart: No TraMineR public function. The closest TraMineR source-level behavior is its internal wtd.var() helper; in general R workflows, weighted variance is usually supplied by a helper package or custom function.
• Mapping note: Sequenzo exposes this as a documented Python helper with method-based estimation, rather than as a wrapper around a TraMineR public API.

Notes

• This is a general weighted statistics function commonly used in R-style workflows.
• It is not specific to TraMineR, but is useful in sequence-analysis summaries.

See Also

• Sequence Summary Statistics Overview maps all summary functions.
• Sequence Summary Statistics vs Sequence Characteristics Indicators explains when to use statistics versus indicators or distances.

Authors

Code: Yuqi Liang

Documentation: Yuqi Liang