fast_history_compute function

Computes cumulative history

Computes cumulative history based on common history values and normalized_tau and mixed_state that are defined for each random cluster / individual.

fast_history_compute(df, normalized_tau, mixed_state, history_init)

Arguments

• df: DataFrame with "state" (integer, 1 and 2 clear state, 3 - mixed state), "duration" (double), "irandom" (integer, 1-based index of a random cluster), "run_start" (integer, 1 for the first entry of the run, 0 otherwise), "session_tmean" (double)
• normalized_tau: DoubleVector A normalized tau value for each random cluster / individual. Thus, its length must be equal to the number of unique indexes in df["irandom"].
• mixed_state: DoubleVector A values used for the mixed state for each random cluster / individual. Thus, its length must be equal to the number of unique indexes in df["irandom"].
• history_init: DoubleVector, size 2. Initial values of history for a run.

Returns

NumericMatrix, size df.nrows() × 2. Computed history values for each state.

Examples

df <- preprocess_data(br_singleblock, state="State", duration="Duration")
fast_history_compute(df, 1, 0.5, c(0, 0))