Videos marked with an (*) contain discussion of new content in ICRFS-Plus™ 12.
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5. TG CS5: heteroscedasticity and varying parameters
5.1 CS5 and Heteroscedasticity
In this video, we introduce varying process variance (heteroscedascity) by development lag within the context of the PTF modelling framework. This is easiest to understand in terms of changes of percentage variability. Generally small payments vary more on a percentage scale than large payments.
We illustrate first using manual hetero analysis. In subsequent videos, we use automatic hetero adjustment.
The modelling of process variance is the fourth component of the PTF modelling analysis. Process variation is a common feature in all real data. This component of the model is just as critical as the changes in trends.
5.2 CS5 and varying parameters
In this study, we examine varying parameters. This concept of varying parameters is close to the idea of exponential smoothing and credibility adjustment.
The model parameters window is discussed along with the relationship between this window and the model graphs (residual and model display).
Basically, for full parameters we give maximum weight to the new observations and zero weight to previous observations (they do not have any relevance to our new trend/level). With varying parameters, information from previous observations also is included when estimating the new 'level' thus we 'smooth' the changes between parameters.
The option reinstate all alpha parameters is also discussed.