Automate the statistical analysis of the serial correlation, model order identification, and exploring patterns in the your time series data.
Time series analysis demands that we pay attention to order, and thus requires a different type of descriptive statistics: time series descriptive statistics, or simply correlogram analysis.
The correlogram analysis examines the time-spatial dependency within the sample data, and focuses on the empirical auto-covariance, auto-correlation, and related statistical tests. Finally, the correlogram is a cornerstone for identifying the model and model order(s).
NumXL comes with numerous functions to calculate the different correlogram statistics (e.g. ACF, PACF, etc.), and present you an intuitive wizard to automates the whole process with a few mouse clicks, and using your data in Excel.
Calculates the sample partial autocorrelation function (PACF).
Calculates the confidence interval limits (upper/lower) for the autocorrelation function.