get_modal_state_sequence()

get_modal_state_sequence() computes the modal (most frequent) state at each time position.

Function Usage

from sequenzo import get_modal_state_sequence
result = get_modal_state_sequence(seqdata, weighted=True, with_missing=False)

Entry Parameters

Parameter	Required	Type	Description
seqdata	✓	SequenceData	Input sequence dataset.
weighted	✗	bool	Use sequence weights.
with_missing	✗	bool	Include missing values in modal computation.

What It Does

• Finds the most frequent state at each time point.
• Supports weighted modal computation.
• Returns a DataFrame describing the modal sequence over time.

Returns

pd.DataFrame.

Examples

from sequenzo import get_modal_state_sequence

modal = get_modal_state_sequence(seqdata, weighted=True)
print(modal)

R Counterpart

• Closest TraMineR function: TraMineR::seqmodst()
• Mapping note: This is a direct conceptual match; Sequenzo wraps modal-state computation with optional weighting and missing-state handling.

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