Post 1 Introduction to Statistical analysis of data with outliers
Post 2 Correlation when outliers in the data.
Post 3 Trend when outliers in the data.
Post 4 Correlation and trend when an outlier is added. Example.
Post 5 Compare Kendall-Theil and OLS trends. Simulations.
Post 6 Detect serial correlation when outliers. Simulations.
The posts are gathered in this pdf document.
Start of post 6: Detect serial correlation in data with outliers
This chapter deals with Monte Carlo simulations that calculate the serial correlation coefficients in noisy data. They are calculated with two different approaches. One uses the noise values, and the other uses the ranks of the noise values. Both approaches work well when the noise is white and when there is serial correlation in the noise. The approach that uses the ranks works much better than the other when there are outliers in the noise. The results are presented as probability density plots.