RollingVar / Computation Layer

Calculate the rolling variance over a sliding window. Similar to pandas.rolling().var() or R's roll_var().

Mathematical form: $σ_{i}^{2} = \frac{\sum _{j = i - w + 1}^{i} w _{j} ( x _{j} - μ ) ^{2}}{\sum _{j = i - w + 1}^{i} w _{j}}$

Common applications:

Financial risk analysis
Process control monitoring
Sensor calibration
Market volatility analysis
Quality assurance
Scientific measurements
System stability monitoring

Note: Square of rolling standard deviation. Measures spread magnitude.

Table

Select

column

The numeric column to compute rolling variance for. Common uses:

Price variability (market risk)
Process variation (manufacturing)
Sensor noise (measurement systems)
Performance dispersion (systems)
Environmental fluctuations

WindowSize

u32

Number of observations (WindowSize) in sliding window. Common periods:

20: Monthly variance (trading)
60: Hourly from minute data
252: Annual variance (trading)

Larger windows provide more stable variance estimates.

Weights

[f64, ...]

Optional weights for window values. Must match window size if provided. Uses:

EWMA variance calculation
Time-weighted dispersion
Custom variance patterns

Affects contribution of each observation to variance.

MinPeriods

oneof

AsWindow

Require complete windows for variance calculation. Ensures statistical reliability by using full window of data. Critical for accurate dispersion measurement and risk assessment.

Period

Value

u32

Minimum number of valid observations (Value) required for variance calculation. Examples:

2: Minimum for variance calculation
window_size/2: Require half window
window_size: Require full window

More observations provide more reliable variance estimates.

Center

bool

false

Window label position. When true, aligns to window center; when false, to end. Effects:

true: Better for historical variance analysis
false: Better for real-time risk monitoring

Name for the new column. If not provided, the system generates a unique name. If AsColumn matches an existing column, the existing column is replaced. The name should follow valid column naming conventions.