get_cross_sectional_entropy()

Computes state distribution and entropy across time positions.

Function Usage

from sequenzo import get_cross_sectional_entropy
result = get_cross_sectional_entropy(seqdata, weighted=True, norm=True, return_format="tidy")

Entry Parameters

• seqdata: SequenceData object.
• weighted: use sequence weights in frequency calculation.
• norm: return normalized entropy.
• return_format: "tidy", "wide", or "dict".

Returns

Time-wise cross-sectional distribution and entropy outputs.

TraMineR Mapping

• Equivalent TraMineR function: TraMineR::seqstatd().

Authors

Code and documentation: Yuqi Liang

See Also

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

References

Ritschard, G. (2023), "Measuring the nature of individual sequences", Sociological Methods and Research, 52(4), 2016-2049. doi:10.1177/00491241211036156.