Time Series Analysis

Understand data, Identify patterns, Develop forecasts.

Fundamentals

Statistische Analyse

Statistical time series models

Classical, robust and explainable.
Ideal for stable patterns and long historical data.

Mobirise

AI based forecasting

Machine Learning and Deep Learning

Powerful for capturing complex patterns.
Well suited for nonlinear and volatile time series.

Mobirise

Forecast quality

Transparent model evaluation

Error metrics, backtesting, diagnostic plots.
This ensures every forecast is understandable and reliable.

Mobirise
Mobirise

Foundations of Time Series Analysis

Time series are sequences of data points measured in chronological order, such as energy consumption, stock prices, production volumes, or sensor readings.
Their value lies in revealing temporal patterns and dependencies that simple trend extrapolation would miss. This enables forecasts that are significantly more accurate and insightful.

Time series analysis examines elements such as:

▸ Trend long term development
▸ Seasonality recurring patterns
▸ Cycles irregular fluctuations
▸ Noise random variation

By combining statistical models with modern AI methods, both stable and highly volatile time series can be forecast with confidence.