Qm
Statistics

Trend-stationary or difference-stationary?

trend-stationarydetrending

A series is Xt=4+0.3 t+εtX_t = 4 + 0.3\,t + \varepsilon_t, where εt\varepsilon_t is white noise.

Is it trend-stationary or difference-stationary, and what single transformation makes it stationary?

Your answer

Solving needs a free account

Answers, streaks and solutions unlock when you are signed in. Reading the question and the hint stays free.

Create a free accountSign in

Discussion

Sign in to join the discussion · reading is open to everyone

💡 Discussion rules

  1. No full solutions here. Hints and approaches only.
  2. Complexity, edge cases and intuition are the point.
  3. Interview experiences are welcome. Respect your NDAs.

Loading discussion…

Learn the concepts

The theory behind this question.

A Benchmarking Harness for New SignalsA Practical Tuning Order for Gradient BoostingA/B TestingThe Abdi-Ranaldo Spread EstimatorDesigning an Ablation Study

Related questions

Does detrending fix a random walk?Why you run an A/B test for whole weeks, not "until it's ready"How big does the A/B test need to be?One guardrail metric out of twenty went redThe test isn't significant, can we just run it longer?
All questions →