Automatic Groove Identification via Bayesian Changepoint Detection
Impute data and estimate groove locations.
Conforming get_grooves_"name" function.
Impute missing data.
Impute missing data.
Example of an average of 2D crosscuts from the Hamby 44 data set.
Fit a robust loess regression
Estimate a posterior distribution of data conditional on zero changepo...
Estimate a posterior distribution of data conditional that there is on...
Estimate a posterior distribution of data conditional on a left groove...
Estimate a posterior distribution of data conditional on a left groove...
Estimate a posterior distribution of data conditional that there are t...
Estimate posterior distributions for the 0, 1, or 2 changepoint case.
Provides functionality to automatically detect groove locations via a Bayesian changepoint detection method to be used in the data preprocessing step of forensic bullet matching algorithms. The methods in this package are based on those in Stephens (1994) <doi:10.2307/2986119>. Bayesian changepoint detection will simply be an option in the function from the package 'bulletxtrctr' which identifies the groove locations.