STL Ruby

gem "stl-rb"

series = {
  Date.parse("2025-01-01") => 100,
  Date.parse("2025-01-02") => 150,
  Date.parse("2025-01-03") => 136,
  # ...
}

Stl.decompose(series, period: 7)

series = User.group_by_day(:created_at).count
Stl.decompose(series, period: 7)

series = [100, 150, 136, ...]
Stl.decompose(series, period: 7)

Stl.decompose(series, period: 7, robust: true)

Stl.decompose(
  series,
  period: 7,              # period of the seasonal component
  seasonal_length: 7,     # length of the seasonal smoother
  trend_length: 15,       # length of the trend smoother
  low_pass_length: 7,     # length of the low-pass filter
  seasonal_degree: 0,     # degree of locally-fitted polynomial in seasonal smoothing
  trend_degree: 1,        # degree of locally-fitted polynomial in trend smoothing
  low_pass_degree: 1,     # degree of locally-fitted polynomial in low-pass smoothing
  seasonal_jump: 1,       # skipping value for seasonal smoothing
  trend_jump: 2,          # skipping value for trend smoothing
  low_pass_jump: 1,       # skipping value for low-pass smoothing
  inner_loops: 2,         # number of loops for updating the seasonal and trend components
  outer_loops: 0,         # number of iterations of robust fitting
  robust: false           # if robustness iterations are to be used
)

gem "vega"

Stl.plot(series, decompose_result)

Stl.seasonal_strength(decompose_result)

Stl.trend_strength(decompose_result)