Spss, Econometrics, Statistics Assignment, Stata, Time Series

Time series analysis is a specific way of analyzing a sequence of data points collected over an interval of time. Such analysis focuses primarily on addressing the structure of the underlying process in order to make predictions, which can be used in finance, the stock market, economics, health, and others. Sometimes time series have more than one variable we can also say multivariate time series.

Data science plays a pivotal role in estimating and optimizing these predictive models, by making use of various statistical techniques:

Baseline Models

• Trend fitting
• Seasonal decomposition
• Autocorrelation
• ARIMA / SARIMA models
• AR Model
• ARIMAX Model
• SARIMAX
• Smoothing
• Autocorrelation and Partial Autocorrelation Analysis

Advanced Model

1. NBeats
2. DeepAR
3. Transformer
4. Facebook Prophet Model
5. RNN and LSTM
6. RandomForest
7. Exponential Smoothing
8. BATS and TBATS
9. FFT
10. LightGBModel
11. XGBModel
12. NHITS Model
13. TransformerModel
14. NLinear Model
15. kalmanForecaster
16. Regression Analysis
17. Accuracy & Testing

Evaluation Matrix

1. Mean Absolute Error
2. Mean Absolute Percentage Error
3. Mean Square Error
4. Mean Absolute Scale Error
5. Scaled Mean Absolute Error

will use depending on the nature of the data and the problem.

let me know the problem